Eight-Disciplines Analysis Method and Quality Planning for Optimizing Problem-Solving in the Automotive Sector: A Case Study

Abstract

Meeting the demands for advanced technology and superior quality in the automotive industry has become essential. Continuous evolution requires a rigorous analysis of every step taken. Customers demand high performance in the technology, design, and digitalization, as well as, of course, quality at a competitive price. To meet these expectations, engineers ensure transparency and trust at every stage of the project, guaranteeing flawless execution. This paper aims to highlight a clear and transparent approach to the 8D analysis method, demonstrating its effectiveness in identifying and solving engineering problems. Furthermore, quality planning and 8D analysis are fundamental pillars of quality management in the automotive industry. To ensure a comprehensive and well-founded approach, this paper combines several research methods: a review of the specialized literature, a hypothetical case study approach, and comparative analysis. The proposed methodology allows for a deep understanding of the concepts addressed, facilitating their applicability in real situations. The main conclusions drawn from this research are that quality planning in an automotive buckle development project has proven to be an essential and complex process, directly influencing the success of the project, the safety of end users, and their satisfaction. The analysis of the implementation of the quality planning process, as previously described, has highlighted several fundamental aspects that must be considered to ensure the success and performance of such a project.

1. Introduction

The automotive industry has emerged as one of the world’s most prestigious sectors, characterized by varied and complex requirements. Meeting the demands for advanced technology and superior quality has become essential. Continuous evolution requires rigorous analysis of the steps taken. Customers expect high performance in the technology, design, and digitalization, as well as, of course, quality at a competitive price. To meet these expectations, engineers ensure transparency and trust at every project stage, guaranteeing flawless execution.

This paper aims to highlight a clear and transparent approach to the 8D analysis method, demonstrating its effectiveness in identifying and solving engineering problems. Operational management and process optimization seek to increase efficiency, improve the quality of industrial products and components, ensure production safety, and boost employee and customer satisfaction. The research goal is to analyze the concepts and techniques of knowledge use in 8D implementation, as well as the integration of knowledge management for product development and manufacturing in the automotive industry.

Eight-Disciplines analysis is a structured problem-solving method used to identify the root cause of defects and to implement corrective and preventive actions, thereby contributing to continuous quality improvement [1,2]. Quality planning is an essential function of quality management that sets the objectives, resources, and actions required to ensure product and process quality [3]. Within quality planning, 8D analysis can be integrated as a problem-management tool during manufacturing or testing, thus ensuring compliance with standards and customer requirements [4]. Both processes rely on iterative improvement cycles (PDCA—Plan, Do, Check, and Act), where planning provides the framework and 8D analysis offers concrete solutions for identified problems [5].

For example, at the Dacia Automobile Plant, quality planning is supported by a high-performance quality management system that includes process standardization and methods such as PDCA and risk analysis; within this system, 8D analysis is used to solve problems detected during manufacturing. In resistance projection of the welding of nuts to sheet metal, the most frequent problems observed are insufficient torque-out (sub-spec joint strength), lack of fusion at one or more projections, thread distortion, and expulsion/spatter due to unstable heat input and force/current/time settings [TWI guidance]. These issues are detected through routine destructive tests, such as minimum tightening torque verification or peel/push-off tests per welding guidelines, complemented where applicable by non-destructive ultrasonic B-scan imaging that correlates the melted area with torque/pull-out strength to localize the incomplete fusion at projections. Corrective actions consist of establishing and validating a robust process window by jointly optimizing electrode force, weld current, and weld time, maintaining electrode/projection integrity (dressing and geometry control), stabilizing fixtures, and adding SPC monitoring; where relevant, qualification follows the ISO 15614-12 for spot/seam/projection welding procedure tests to ensure repeatability and compliance. After parameter optimization, joints meet the torque-out criteria while eliminating expulsion and thread damage, as confirmed by torque and peel tests; additionally, when used, ultrasonic indications consistent with full-fusion nuggets at each projection [6].

In the automotive industry, Automotive Core Tools (including APQP, FMEA, and 8D) are used for quality planning and problem management, ensuring compliance with the requirements of IATF 16949 standards [7,8,9].

The complementarity between 8D and quality planning is supported by recent industrial studies: in a case published in Engineering Failure Analysis, integrating 8D with FMEA and Value Stream Mapping within a process improvement program reduced defects from 1071 ppm to ≈0, confirming the combined effect of root cause analysis and quality planning on product and process performance. At the organizational level, a longitudinal investigation showed that the systematic use of 8D reports together with training significantly shortened problem resolution time year-on-year, which correlated with reduced defect recurrence and increased customer satisfaction through faster feedback and process stabilization. In automotive manufacturing, the application of 8D on rear seat and related component lines eliminated critical defects after optimizing parameters and updating control plans, demonstrating how 8D (D3–D7) and planning tools (FMEA, Control Plan, SPC) act synergistically to reduce scrap and complaints [10]. In the case study presented in Section 4, the 8D method was applied to a seat-belt buckle riveting nonconformity (Fisker 2332, P/N 63266666E), demonstrating RCA and CAPA within quality planning (see Figures 4–12), or, alternatively, we now cite specific published 8D case studies in the automotive industry to substantiate the claim. In recent years, quality management has become an essential pillar of project management success, regardless of the field of activity. In a globalized economy with fierce competition, the quality of a project’s deliverables represents a significant differentiator. From the perspective of quality management theory, quality planning is a critical phase, an integral part of management processes, alongside resource, cost, and risk planning. Without rigorous planning, projects may face difficulties such as additional costs, missed deadlines, or beneficiary dissatisfaction. Moreover, increasingly strict requirements for sustainability and compliance with international regulations have emphasized the need for clear and well-documented processes for quality management.

Sustainability in the automotive industry involves integrating practices that reduce environmental impact and optimize resource use throughout the product lifecycle. In the context of quality and problem-solving, sustainability is reflected in the following:

• Reducing waste by identifying and quickly correcting defects (e.g., a defective buckle detected and efficiently remedied);
• Implementing energy-efficient processes and using technologies that minimize resource consumption;
• Promoting sustainable design and green mobility (e.g., recyclable components, reducing emissions in manufacturing).

Automotive companies adopt sustainability strategies to meet regulatory requirements, increase competitiveness, and satisfy environmentally conscious customer demands.

The connection between the three concepts:

Eight-Disciplines analysis contributes to quality improvement and defect reduction, thus supporting the objectives of quality planning and sustainability. Efficient quality planning helps prevent problems from occurring, while integrating sustainability principles ensures that the implemented solutions are effective not only economically but also environmentally and socially.

This paper highlights the applicability of the Eight-Disciplines (8D) problem-solving method as a structured, team-oriented approach widely used in automotive to identify root causes, implement corrective actions, and prevent recurrence; in this article, 8D refers to steps D0–D8 (Plan; Team; Problem description; Containment; Root cause; Corrective action selection; Implementation/validation; Prevention; Team recognition) as standardized in industry guidance. Key variables in data management and collection, as well as in handling customer complaints, are identified. In the first stage, the customer’s request is promptly addressed through an ERA analysis. Subsequently, the SPD method is used to clearly identify and define the symptom or problem. Once the issue is established, various tools are applied to assess the degree of nonconformity and identify the root cause, using Ishikawa analysis, Pareto diagrams, and graphical evidence based on data obtained from clients and dealers. This paper also aims to contribute to a better understanding of the complexity of the quality planning process by addressing both theoretical and practical aspects. Our approach intentionally integrates Ishikawa (systematic cause exploration), Pareto (vital–few prioritization), and SPC capability indices (Cp/Cpk) for quantitative validation. This combination aligns with the ASQ “Seven Basic Quality Tools” guidance and NIST SPC practice, enabling us to (i) focus on the few causes driving most defects, (ii) avoid omissions/bias in RCA, and (iii) confirm effectiveness via improved capability (Cpk > 1.33) after implementation, as shown in Figures 4–12 of our case study.

The automotive sector requires disciplined, evidence-based problem-solving to address recurring nonconformities in safety-critical operations, under stringent customer and regulatory requirements that commonly prescribe or expect structured approaches such as the Eight Disciplines (8D). The 8D method—originating at Ford as a team-oriented, standardized process—combines rapid containment with verified root-cause analysis and long-term corrective/preventive actions to eliminate recurrence in complex production systems. In parallel, OEM and supplier quality systems aligned with IATF 16949 increasingly require the use of customer-specified formats for complaint resolution (e.g., 8D), reinforcing the need for clear, auditable problem-solving documentation in the supply chain.

Research Gap and Contribution: While 8D is widely adopted in automotive manufacturing and often requested by OEMs for supplier responses, many publications emphasize procedural description over quantitative validation and integrated quality-planning linkages, limiting the practical transferability of lessons learned. This study addresses that gap by presenting a transparent, step-by-step 8D case on a seat-belt buckle nonconformity, integrating APQP/FMEA practices and statistical capability evidence (e.g., Cp/Cpk improvement beyond common automotive benchmarks) to demonstrate verified effectiveness and prevention of recurrence within an IATF-consistent framework. Specifically, the case quantifies pre-/post-improvement performance and shows how corrective and preventive actions were standardized across documentation (P-FMEA and Control Plan) and sites, strengthening both compliance and operational robustness.

Objectives: This work (i) motivates the necessity of a structured 8D process in a safety-critical context, (ii) evidences effectiveness with capability metrics and defect–risk reduction, and (iii) codifies prevention and the read-across within core quality planning to support sustained conformity in serial production.

2. The Literature Review

The Literature Review for the 8D Analysis Method

The 8D method (“Eight Disciplines”) is a structured, team-oriented approach for solving recurring problems, with a focus on identifying root causes and implementing corrective and preventive actions. It was initially developed in the automotive industry but has been widely adopted in various sectors, including manufacturing, healthcare, services, and public administration [11,12,13].

Structure of the 8D Method

The 8D method involves going through eight main steps:

• D0: Planning—defining the plan of approach for the problem.
• D1: Team Formation—selecting a multidisciplinary team with relevant expertise.
• D2: Problem Definition and Description—detailed problem analysis using techniques such as 5W2H (who, what, where, when, why, how, and how much).
• D3: Implementation of Containment Actions—temporary measures to limit the impact of the problem.
• D4: Identification of Root Causes—use of analysis tools such as the “5 Whys” and the cause–effect (Ishikawa/Fishbone) diagram.
• D5: Selection and Verification of Permanent Corrections—validation of the proposed solutions.
• D6: Implementation and Validation of Corrective Actions—putting the solutions into practice and evaluating their effectiveness.
• D7: Prevention of Recurrence—amending procedures to prevent recurrence of the issue.
• D8: Team Recognition—formal acknowledgment of the collective effort [14].

Results and Demonstrated Benefits in the Literature

Reduced Problem-Solving Time: Case studies in the automotive and manufacturing industries show that after implementing the 8D method and staff training, the time required to identify and resolve problems has significantly decreased in subsequent years, leading to resource savings and reduced scrap rates [15,16,17].

Improved Product and Process Quality: Implementing 8D has led to decreased defects, increased customer satisfaction, and optimized internal processes [18].

Systematic and Collaborative Approach: The method promotes teamwork and the use of statistical and analytical tools, increasing the efficiency and robustness of identified solutions [19].

Identified Limitations and Challenges

• Need for Training: The effectiveness of the method depends on the team’s training level and discipline in following the steps [20].
• Limited Applicability without Management Support: Long-term success requires active management involvement and the integration of 8D into the organizational culture [21].
• Empirical Evidence: Some of the literature highlights a lack of extensive empirical studies, with much of the body of work focusing on process description and less on statistical results analysis [22].

Conclusion: The 8D method is recognized as an effective tool for solving complex and recurring problems, with proven results in reducing defects and increasing process efficiency. The literature emphasizes the importance of rigorous step-by-step application, team training, and managerial support to fully harness the benefits of this method [23].

The Literature Review: Quality Planning and 8D Analysis in the Automotive Industry

Quality planning is an essential component of quality management in the automotive industry, aimed at ensuring that products and processes conform to customer requirements and international standards [24]. The literature highlights the following key aspects:

• Standardization and Systematic Approach: Quality planning processes are structured based on PDCA (Plan–Do–Check–Act) and SDCA (Standardize–Do–Check–Act) cycles, ensuring continuous improvement in product and service quality [25].
• Core Tools: Essential tools used in quality planning include APQP (Advanced Product Quality Planning), FMEA (Failure Mode and Effects Analysis), MSA (Measurement System Analysis), PPAP (Production Part Approval Process), and SPC (Statistical Process Control) [26].
• Integration of Strategic Objectives: The quality plan is aligned with organizational strategy, deployed at all operational levels and supported by cross-functional actions for continuous improvement [27].
• Management and Multidisciplinary Team Involvement: The success of quality planning depends on active management involvement and collaboration between departments, as well as the ongoing training and education of personnel [28].

Eight Disciplines Analysis in the Automotive Industry

The 8D (Eight Disciplines) method is recognized as one of the most effective approaches for solving recurring and complex problems in the automotive sector. Key findings from the literature include the following:

• Origin and Evolution: Eight Disciplines was initially developed by Ford Motor Company and became a standard approach in the automotive industry for systematically addressing critical nonconformities [29].
• Eight Disciplines’ Process Structure: The method involves eight disciplines, from initial planning and team formation to root cause identification, corrective action implementation, and prevention of recurrence. An additional stage, D0 (planning), is considered essential for process success [30].
• Demonstrated Benefits: Studies show that 8D implementation leads to reduced problem-solving times, fewer defects, higher customer satisfaction, and optimized internal processes [31].
• Complementary Tools: In practice, the 8D method is often used alongside other quality tools such as Six Sigma, FMEA, and statistical analysis to ensure a robust and efficient approach to technical and organizational issues.
• Challenges and Limitations: The literature points out the need for team training, management involvement, and integrating 8D into the organizational culture to achieve sustainable results [32].

Comparative 8D vs. DMAIC

Eight Disciplines and DMAIC are both structured, evidence-based approaches—8D is optimized for customer-facing nonconformities requiring immediate containment and documented prevention of recurrence, while DMAIC is a Six Sigma framework for sustained process improvement and variability reduction.

Aspect	8D	DMAIC
Primary use	Structured response to a specific defect/complaint with immediate customer protection and verified root cause elimination.	Data-driven improvement in existing processes to reduce variation and defects over time.
Steps	D0–D8 with explicit interim containment (D3) and prevention of recurrence (D7).	Define–Measure–Analyze–Improve–Control, focused on measurement, analysis, and sustained control.
Teaming	Multidisciplinary team chartered to solve and close a discrete problem with auditable documentation.	Cross-functional project team executing an improvement roadmap with statistical rigor.
When to choose	Safety/quality incidents, customer complaints, and recurring defects requiring rapid containment and standardized closure.	Process capability uplift, yield/cycle-time reduction, and chronic variation problems.

The Literature Synthesis and Current Trends

• Integration of Core Tools: The automotive industry uses an integrated set of tools for quality planning and management, and 8D is a key part of this ecosystem [33].
• Focus on Continuous Improvement: Both quality planning and 8D analysis are based on the principle of continuous improvement, aiming to prevent defect recurrence and increase competitiveness [34].
• Recent Case Studies and Research: Recent studies highlight the successful implementation of the 8D method for solving specific issues (e.g., automotive component defects, and durability testing optimization) and its role in developing a quality- and innovation-oriented organizational culture [35].
• An automotive review and application of the “8D” method (2022) includes a dedicated comparison of 8D versus DMAIC and discusses tool integration within 8D, highlighting contexts where each method excels [36,37].
• An automotive seat belt case (2020, open access) reports 8D implementation with quantified defect reduction from 60 pieces/month to 0 within four months and horizontal deployment (“yokoten”) post-closure [38,39].
• Authoritative overviews of the structure and intent of 8D are used to standardize terminology and emphasize the method’s focus on interim containment and prevention of recurrence [26,40].
• Practitioner syntheses comparing 8D and DMAIC are cited to clarify the prevention versus control distinction and selection criteria in industrial settings [41].

Conclusion: Quality planning and 8D analysis are fundamental pillars of quality management in the automotive industry. The literature underlines the importance of a systematic approach, the use of correlated tools, and involvement at all organizational levels to achieve operational excellence and customer satisfaction.

3. The Concept and Methods

3.1. The Contribution of 8D Analysis to Quality Planning and Sustainability in the Automotive Industry

➢

Eight Disciplines’ Analysis and Quality Planning

Integration into Quality Management: The 8D method is an essential tool in quality planning, used for identifying, analyzing, and eliminating the root causes of recurring problems in automotive production processes [42,43].

Structured Approach: Through its clear steps—from problem definition, team formation, and root cause analysis to the implementation and validation of corrective actions—8D ensures a systematic and well-documented resolution of nonconformities, enabling continuous improvement in processes and products [44].

Prevention of Recurrence: One of the key outcomes of the 8D method is the modification of procedures and management systems to prevent problem recurrence, thereby strengthening long-term quality control [45].

Synergy with Other Tools: The 8D method is often used alongside tools such as FMEA, SPC, or Six Sigma, contributing to robust quality planning and the achievement of performance and reliability objectives [46].

➢

Eight Disciplines’ Analysis and Sustainability

Reducing Waste and Scrap: By quickly identifying and correcting defect causes, the 8D method helps to reduce material losses and resources consumed in remediation processes, thus supporting sustainability objectives [47].

Optimizing Resource Use: Implementing permanent corrective actions and preventing defect recurrence leads to more energy-efficient processes and reduced raw material consumption.

Improving Product Reliability: By increasing the quality and reliability of automotive components, the need for repairs and replacements is reduced, which in turn diminishes negative environmental impact [48].

Supporting an Organizational Culture Oriented Toward Continuous Improvement: The 8D method fosters collaboration, organizational learning, and responsibility for quality and the environment, fundamental elements for long-term sustainability [49].

➢

Demonstrated Benefits in the Automotive Industry

• Reduced costs related to defects and warranties;
• Increased customer satisfaction through more reliable products;
• Creation of a lessons-learned database, useful for preventing future problems;
• Enhanced team ability to efficiently manage nonconformities and make data-driven decisions.

Conclusion: Eight Disciplines analysis is a pillar of quality planning and a catalyst for sustainability in the automotive industry, ensuring not only the efficient resolution of problems but also their prevention, resource optimization, and the development of an organizational culture oriented toward operational excellence and environmental responsibility.

3.2. Methodology Used

To ensure a comprehensive and well-founded approach, this paper combines several research methods:

✓

A Literature Review: A detailed analysis of relevant materials was conducted, including academic work, scientific articles, and internationally recognized standards such as ISO 9001 and PMBOK. This review provides a solid theoretical foundation and outlines the main concepts related to quality planning.

✓

Hypothetical Case Study Approach: A generic scenario, representative of various fields, was created in order to analyze the quality planning process in a practical context. This case study covers all relevant stages, from requirements identification to performance evaluation.

✓

Comparative Analysis: Within this study, best practices identified in the literature are discussed and compared to the challenges and solutions presented in the generic example. The proposed methodology enables a deep understanding of the addressed concepts, facilitating their applicability in real situations; at the same time, the work offers a generalized model that can be adapted according to the specific requirements of a project.

Choosing the Case Study Method

The case study method was chosen because of its relevance for in-depth, contextualized analysis of a specific process—in this case, quality planning in projects. The case study enables detailed exploration of either a hypothetical or real situation, focusing on understanding the complexity of the involved processes and identifying challenges and solutions. This method is suitable for research aimed at applied aspects, such as the following:

-

Testing Theoretical Models:   The case study method allows for the application of concepts from the literature in a practical context.

-

Identifying Problems and Solutions:   By simulating a generic project, challenges encountered in quality planning can be analyzed, and solutions can be proposed.

To ensure the general relevance of the conclusions, the hypothetical case study was designed to be applicable across multiple industries (construction, IT, and manufacturing). For example, in the case of a software application, quality may be defined by a low number of bugs and adherence to delivery deadlines, while for a commercial building, quality is defined by compliance with safety regulations and the client’s aesthetic requirements.

3.2.1. Description of the Tools Used

Document Analysis

Document analysis was employed to understand the concepts, standards, and tools used in quality planning. The sources examined include the following:

• ISO Standards (e.g., ISO 9001): These provide a basis for defining and assessing quality requirements.
• Manuals and Best Practice Guides (e.g., PMBOK): These were analyzed to identify relevant processes and tools.
• Previous Studies: Published research offers perspectives on the challenges and solutions applied in real projects.

For example, the PMBOK guide suggests the use of benchmarking to compare a project’s performance with industry best practices—an instrument that will be illustrated in the case study.

Hypothetical Interviews

To simulate the validation of proposed solutions, hypothetical interviews were conceived of with three categories of experts:

• Project Managers: To understand the practical perspective on challenges in quality planning.
• Quality Control Specialists: To identify preferred methods for quality monitoring and evaluation.
• Stakeholders: To assess how project deliverables’ quality and value are perceived.

The interviews included open-ended questions such as the following: What are the most frequent obstacles encountered in implementing the quality plan? What tools do you consider most effective for defect prevention? How do you evaluate the success of a project from a quality perspective?

3.2.2. Research Limitations

As with any methodological approach, this research presents several limitations that should be considered:

Generalizability of Conclusions

The case study is hypothetical, which limits the direct applicability of the conclusions to real projects. For example, the specifics of an automotive project may differ significantly from those of an IT project, even if both follow similar quality planning principles.

Subjectivity of Hypothetical Interviews

The hypothetical interviews reflect general expert perspectives but cannot fully capture the complexity of real-life situations. This may influence the validity of the proposed solutions.

Limited Access to Real Data

For the purposes of the case study, although real data from a specific project were used, the analysis is limited by a lack of additional concrete examples from documentation or project reports.

Lack of Quantitative Evaluation

The research focused on qualitative methods, without detailed statistical analysis of the results. For example, the cost of quality was not directly evaluated, which reduces the ability to quantify the benefits of quality planning.

3.2.3. Case Selection, Sampling, and Data Collection Protocol

Case design and selection

This is a single, embedded case study focused on a seat-belt buckle riveting defect at Romania Rovinari Seatbelts (RRS), selected as an information-rich, safety-critical incident that enables theory-driven replication of 8D practices in an IATF-conformant environment.

The rationale follows purposeful/theoretical sampling: the case exhibits clear CTQs (rivet diameter and joint force), observable process parameters, and complete 8D traceability (D2–D7), which are prerequisites for analytic (not statistical) generalization in case research.

Context and timeframe

Complaint date 16 May 2023; affected lot manufactured 30 March 2023; client Fisker; supplier Norma; detection at customer; confirmation of 8.57 mm NOK diameter in-plant on 24 May 2023.

The study window spans D3 containment through D7 prevention, covering interim screening, parameter trials, and capability re-establishment.

Case-study protocol, database, and audit trail

A protocol enumerating research questions, data sources, instruments, and decision rules was used, and a case database (documents, raw data, MSA records, SPC outputs, and 8D logs) was maintained to ensure reliability and replicability.

The reporting preserves a chain of evidence from complaint through D7 closure so that readers can trace each finding back to its originating record.

Ethics and confidentiality

No human subjects were involved; industrial data are confidential and reported as exact counts or bounded ranges with full methodological detail to satisfy transparency while protecting proprietary information.

3.3. Example of a Gantt Chart for Quality Planning in an Automotive Project (Automotive Buckle)

A Gantt chart is an essential tool for planning and monitoring activities in automotive projects, including the development and quality assurance of components such as automotive buckles. It allows for a clear visualization of project phases, responsibilities, dependencies, and deadlines, facilitating team coordination and compliance with quality requirements. The main stages of quality planning for an automotive buckle project, Figure 1.

Benefits of Using a Gantt Chart

-

Project Visibility: All team members clearly see the steps, responsibilities, and deadlines.

-

Identification of Dependencies: The chart makes it easy to observe activities that depend on each other and which may cause delays.

-

Progress Monitoring: Regular updates enable quick correction of deviations from the plan.

-

Improved Collaboration: Facilitates communication among design, quality, production, and management teams.

This example is simplified but can be detailed and expanded to include more activities. Such a chart helps the team understand the specific steps in the quality planning process and track progress visually.

3.4. Example of a Quality Requirements Matrix

A quality requirements matrix is useful for organizing and visualizing the specific requirements that must be fulfilled within the project, see Figure 2. It can include standards related to safety, reliability, and performance for auto components such as automotive buckles.

This matrix can be extended to include other specific requirements for automotive components. It helps the project team to clearly understand the quality expectations and standards to be followed. For research methodology in the automotive field, the quality standards that should be included are those that ensure product and process compliance with customer requirements, legal regulations, and international best practices. These standards are classified according to their level of application (national, European, or international) and by the type of product or service.

This section describes the 8D workflow applied to the buckle complaint: For each discipline, we list the inputs, activities/tools, outputs, and the exact location in the Results Section where outcomes are presented. Then, we label existing content under these subheadings with standardized micro-blocks:

• D1 Team and Roles—inputs: functions and stakeholders; activities: RACI, cadence; outputs: team charter → Results Section 5.
• D2 Problem Description—inputs: 5W2H, check sheets; activities: Pareto, Ishikawa; outputs: CTQs and baseline metrics → Results Section 5.1.
• D3 Interim Containment—inputs: stock/field status; activities: 100% inspection, shipment holds; outputs: customer protection status → Results Section 5.2.
• D4 Root Cause—inputs: process parameters, gauge data; activities: 5 Whys, capability snapshot; outputs: verified causes → Results Section 5.3.
• D5 Solution Selection—inputs: verified causes; activities: options matrix, FMEA; outputs: selected parameter set → Results Section 5.1.
• D6 Implementation/Validation—inputs: chosen settings; activities: pilot runs, acceptance criteria; outputs: before/after metrics → Results Section 5.2.
• D7 Prevention—inputs: residual risks; activities: P-FMEA/control plan, read-across; outputs: sustainability criteria (e.g., Cpk ≥ 1.33 over time) → Results Section 5.3.
• D8 Lessons Learned—inputs: final KPIs; activities: standardization, knowledge capture; outputs: lessons and closure → Results Section 5.

APQP–8D Integration and Evidence: For each 8D discipline, the team recorded the corresponding APQP phase, Core Tool updated, and the quantitative evidence required for closure; D2–D4 feed PFMEA baselines, D5–D6 trigger capability studies with MSA-qualified gauges and PPAP trial data, and D7 mandates PFMEA re-ranking and Control Plan revisions with updated reaction plans and read-across, per recognized 8D–PFMEA interaction guidance and APQP Phase 5 practice.

Quality Planning (APQP/Core Tools) is integrated with each 8D step, using an explicit APQP–8D linkage matrix, quantified risk/capability deltas (RPN and Cp/Cpk), and documented PFMEA→Control Plan updates in line with IATF expectations.

APQP Phase	Main Core Tools	8D Step(s) Integrated	Evidence to Report
Phase 3: Process design	PFMEA, Process Flow, preliminary Control Plan	D2–D4 (problem definition, root cause)	Link failure modes/causes to CTQs; baseline S/O/D and RPN; initial controls and gaps
Phase 4: Validation	MSA, SPC, capability studies, PPAP trials	D5–D6 (select and validate solutions)	Trial matrix and acceptance criteria; before/after Cp/Cpk; MSA summary for gauges used
Phase 5: Feedback and corrective action	Lessons learned, PFMEA re-ranking, Control Plan revision, Read-Across	D7–D8 (prevent recurrence, standardize)	RPN deltas and control changes; updated reaction plans; audit evidence and global alerts/read-across logs

4. Case Study: Quality Planning in the Automotive Buckle Manufacturing Process—8D Analysis

This section presents the applicability of 8D in the automotive field and the delineation of stages for process optimization. The best variables in the process of managing and collecting data and customer complaints are identified. In the first phase, the customer’s request is urgently addressed through an ERA analysis. SPD is used to identify and define the symptom/problem. Once the problem is identified, tools are used to measure the degree of defectiveness, and identify and verify the root cause using Ishikawa analysis, Pareto, and graphical evidence based on data collected from customers and dealers. Eight Disciplines Problem-Solving analysis is a structured methodology used to identify, correct, and prevent recurring problems in industrial and business processes.

The problem symptom generates an unwanted effect and was identified using the necessary information regarding functionality effects and extended ones. On 16 May, a customer reported insufficient riveting on a buckle compared to the required standard for seat belt assembly, on part number 63266666 E—buckle subassembly for rear, exterior. The rivet diameter is smaller than the standard specification, nonconforming dimension (NOK): 8.6 mm versus conforming dimension (OK): 12.3 mm [50].

An urgent response action was developed to protect the customer and initiate the 8D process.

Specifications and Steps of the 8D Method:

D1—Team Formation

The 8D approach requires the formation of a well-organized team, equipped with the knowledge and resources necessary to identify the root cause of the problem. Members of this team must be familiar with the process, as well as with the specific tools and techniques to efficiently solve the identified problem. An interdisciplinary team with relevant expertise for the problem is assembled. The responsibilities of each member are defined.

a. Objective:

• A team of experts is formed who have the necessary knowledge about the product, process, and problem;
• The responsibilities of each member are defined;
• It is ensured that all team members have a common understanding of the 8D methodology.

b. Selection of Team Members:

The team must be formed of people with relevant competencies, including the following:

• Quality manager—expert in defect analysis and quality requirements;
• Process engineer—understands the production flow and can identify potential causes;
• Product/design engineer—knows technical specifications and can verify if the problem is design-related;
• Operators and technicians—have practical experience with the product and can provide information about encountered problems;
• Supplier manager (if applicable)—analyzes if the problem comes from the supply chain;
• Manager or team leader—coordinates the process and ensures methodology compliance.

c. Team Structure and Organization:

• A team leader is designated, responsible for managing the investigation and facilitating discussions;
• Clear communication channels are established between members;
• Necessary resources for investigation are defined (time, equipment, data access, etc.);
• Regular meetings are planned to monitor analysis progress.

d. Tools Used in D1:

• RACI Matrix: (R (Responsible)—the person who actually performs the task or activity. A (Accountable)—the person who has final responsibility and approves the result. C (Consulted)—people who provide consultation or expertise, being consulted during the process. I (Informed)—people who need to be informed about the progress and results of the activity, which helps to clarify the responsibilities of each member.
• Skills Map: To ensure a well-balanced team.
• Communication Plan: Establishing meeting and reporting frequency.

e. The Importance of a Well-Structured Team:

When the team is not well-formed, problems can arise: lack of necessary expertise → difficulties in identifying the cause; process delays → inefficient or incomplete solutions; lack of collaboration → corrective measures are not implemented correctly.

Therefore, the following team is formed: An engineer who interfaces with the customer, a quality engineer, a manufacturing process engineer, a maintenance engineer, and a maintenance and manufacturing coordinator who is also the team leader.

D2—Problem Description

a. Purpose of D2:

• To describe the problem clearly and in detail;
• To eliminate assumptions and base the analysis on concrete data;
• To establish the impact of the problem on the product, process, and customer.

b. Problem Identification:

In a clear manner, using techniques such as “5W2H” (Who, What, Where, When, Why, How, and How Much), the team must systematically answer fundamental questions related to the problem, thus facilitating the identification of the root cause and establishing efficient corrective actions. The 5W2H method, applied for a complete and objective description, see Figure 3, answers the following:

c. Data Collection and Analysis

To better understand the problem, detailed information is gathered:

• Production Data: Lots, serial numbers, involved suppliers.
• Process Parameters: Temperature, pressure, operating time, etc.
• Historical Data: Previous similar problems, corrective actions applied.
• Customer Complaints: Feedback and defect reports.

d. Tools Used in Stage D2

• Pareto Diagram: To identify the most frequent cause.
• Ishikawa (Fishbone) Diagram: To analyze possible causes.
• Check Sheet: For systematic data collection.
• Photos and Samples: To clearly illustrate the defect.

For the case study under discussion, in the D2 problem description, we include the following:

• Report Date: 16 May 2023.
• Client: Fisker Inc.
• Supplier: Norma (an industrial supplier specialized in components for various industries).
• Problem: insufficient riveting on the buckle, delivered by Autoliv Rovinari (Romania Rovinari Seatbelts—RRS) and Norma for seatbelt assembly.
• Part Number: 63266666 E—rear buckle subassembly, exterior.
• Affected Model: Fisker 2332.
• Production Date: 30 March 2023 (manufactured in the plant).
• Detection: the problem was discovered by Fisker.
• Defect Description: The rivet diameter was smaller than the standard specification, see Figure 4.
• NOK (nonconforming) Dimension: 8.6 mm/OK (conforming) dimension: 12.3 mm.
• Date of Part Receipt in the Plant: 24 May 2023.
• Confirmation of NOK Dimension in the Plant: 8.57 mm.

D3—Immediate Corrective Actions

Temporary measures are implemented to minimize the impact of the problem on production and customers, and to stop the defect from spreading in the process until the root cause is identified and eliminated. This ensures that the problem does not worsen before a complete solution is found.

Containment actions are temporary steps taken to prevent the delivery or use of defective products until the root cause is found and eliminated:

Identification and Isolation of Nonconforming Parts

• Parts produced on 30.03.2023 were isolated and blocked at the supplier;
• Visual and dimensional inspection was performed to separate NOK parts from OK parts;
• Previous and subsequent batches were checked to assess if the issue was widespread.

Notification of Involved Parties

Norma was informed by Fisker about the detected issue. The notification was received, and an action plan was initiated.

Supplementary Inspections and Temporary Checks

• Dimensional measurements on suspect parts:
• NOK dimension: 8.6 mm (confirmed 8.57 mm)/OK dimension: 12.3 mm;
• Implementation of a 100% filter for parts in stock;
• Additional checks in production to prevent new defect occurrences.

Stopping the Affected Deliveries

• Parts in stock and in transit were blocked until a solution was identified;
• Ford Saarlouis was notified to take action on parts already assembled.

Additional Short-Term Controls

• Adjustment of the riveting equipment parameters to improve pressure;
• Training operators to visually inspect the rivet before use;
• Use of a checking template for more precise measurements.

Validation of the Effectiveness of Containment Actions

• Continuous monitoring of parts in production;
• A 100% visual and dimensional inspection to prevent the delivery of nonconforming products;
• Customer confirmation that temporary actions are effective.

D4—Identification of the Root Cause

Applying the 5 Whys Method:

Problem Identified: The rivet has a smaller diameter than specified, which reduces mechanical strength.

• Why does the rivet have a smaller diameter?
• Because the riveting process does not apply enough pressure.
• Why does the riveting process not apply enough pressure?
• Because the equipment settings are incorrect.
• Why are the equipment settings incorrect?
• Because proper calibration of the riveting force was not performed.
• Why was the calibration of the riveting force not performed correctly?
• Because there is no clear standard for regular checks.
• Why is there no clear standard for regular checks?
• Because the preventive maintenance procedure is incomplete or not followed.

Identified Root Cause:

The identified root cause was the lack of a strict calibration and maintenance procedure for the riveting equipment.

The actual root cause is then confirmed by tests and data analysis. After reviewing the process and inspecting the equipment, the following can be stated:

• It was confirmed that the riveting equipment settings were incorrect, which led to inadequately deformed rivets and, thus, a smaller final diameter;
• Additionally, the lack of regular inspections allowed this problem to go undetected for some time.

Conclusion: The main cause of the problem is defective calibration and a lack of periodic maintenance of the riveting equipment. This led to insufficient riveting, resulting in parts with a smaller diameter that could not withstand the required forces, see Figure 5.

The chart clearly shows that the rivet with a diameter of 8.6 mm (NOK) has significantly lower strength compared to the 12.3 mm (OK) rivet. The strength is proportional to the cross-sectional area of the rivet, which explains the large difference in capacity between the two variants. This confirms that the smaller rivet is not able to withstand the same forces, which can lead to assembly failure.

Moreover, the process is completely incapable, with a very low Cpk. Most parts are below the minimum allowable limit (12.3 mm), resulting in a high percentage of rejects, see Figure 6.

Possible Solutions: Increasing the process average and reducing variation to bring the distribution into the acceptable area.

Bolt shear stress:

-

NOK bolt diameter: 8.6 mm;

-

Maximum acceptable force: 20 kN;

-

Measured force distribution (realistic example for a non-capable process);

-

LSL (lower specification limit) and USL (upper specification limit) for capability [50] (Figure 7).

A normal distribution of the measured forces is considered, and we will calculate Cp and Cpk:

Cp = (USL − LSL)/6σ; Cpk = min ((USL − μ)/3σ, (μ − LSL)/3σ)

where

-

μ is the mean of the measured forces;

-

σ is the standard deviation.

The calculation results show that this process is NOK (not capable):

Cp = 0.67 → the variability in the process is too high compared to specifications. A capable process must have Cp ≥ 1.33.

Cpk = 0.67 → the mean is too close to LSL or USL, which confirms that the produced parts 598 are not reliable.

Probability of failure = 97.7% → almost all produced pieces have forces below 20 kN, which is unacceptable.

This result demonstrates that the smaller diameter rivet cannot provide the minimum necessary force, confirming the conclusions from the previous chart.

Description of the Riveting Process

The riveting process illustrated in the image is carried out by an orbital riveting machine, which ensures the controlled deformation of the rivet to fix the assembled components, see Figure 8: riveting process—part positioning and DOF constraints. The part nest follows the 3-2-1 locating principle to fully constrain the subassembly during orbital riveting: the primary data consists of three hardened support pads in the base nest that arrest translation Tz and rotations Rx, Ry by establishing a stable reference plane under the part (three constraints). The secondary data consists of two lateral locators (pins/buttons) referenced to the dominant side face, which arrest translation along X and rotation Rz (two constraints). The tertiary data consists of a single end stop contacting the orthogonal side face, arresting the remaining translation along Y (one constraint). Clamping is applied by a top pneumatic clamp (or toggle) acting along −Z to seat the part against the primary supports without adding location DOF; clamp force is aligned to drive the part onto its locators, per standard locating and clamping principles. The riveting stack is aligned on the Z-axis: the back-up anvil under the rivet head and the orbital riveting head above the joint are coaxial, while the orbiting tool operates with a small inclination to form the head; therefore, fixturing must preserve coaxiality and prevent in-plane slip during load application. In this configuration, all six degrees of freedom are constrained: Tz, Rx, and Ry by the three base supports; Tx and Rz by the two side locators; and Ty by the end stop, while the clamp ensures repeatable seating without over-constraint.

1. Key components of the process:

-

Riveting Controller: The electronic equipment that controls the parameters of the riveting process, such as force, duration, and position.

-

Orbital Assembly Group: The physical mechanism that applies the necessary pressure and movement for the deformation of the rivet.

-

Riveting Station: The structure where the parts are positioned and where the actual process takes place.

2. Stages of the riveting process:

(a)

Positioning the parts—the components that need to be fixed are placed in the supporting device;

(b)

Placing the rivet—the rivet is inserted into the hole of the components;

(c)

Activating the riveting group—the system applies controlled pressure to the end of the rivet;

(d)

Controlled deformation of the rivet—the rivet is pressed and shaped in such a way as to create a solid joint;

(e)

Parameter verification—the riveting controller monitors the process and confirms whether the force and deformation are within acceptable limits.

A correct riveting process must ensure that the rivet is sufficiently deformed to provide a secure joint without damaging the components.

D5—Development and Selection of the Permanent Solution

At this stage, permanent corrective measures were established to eliminate the root cause. The feasibility and effectiveness of the proposed solutions are evaluated.

The D5 stage includes the following:

• Evaluation of possible solutions—analyze various corrective action options, taking into account costs, required resources, and the impact on the process;
• Implementation of the corrective action—after selecting the solution, ensure that everyone involved in the process understands and follows the new procedure or practice;
• Monitoring the effectiveness of the corrective action—continuously assess whether the corrective measure has had the desired impact and if the problem has truly been resolved.

Proper implementation of this stage is essential for the success of the 8D process, because without effective corrective actions, the problem may recur.

1. Identification and selection of solutions:

• The collected data are analyzed to understand the root cause of the problem;
• Effective solutions are chosen to eliminate or reduce the impact of the defect.

2. Implementation of corrective actions:

• Process parameters are defined and adjusted based on experimental analysis;
• Specifications are set according to clear objectives, such as stroke depth (S), process time (T), applied force (F), height after deformation (H), and total length before deformation (U).

In Figure 9, the comparison is shown between the initial parameters (at the time the complaint was reported) and those adjusted after analysis.

Verifying the effectiveness of the measures:

-

Analyze the results to see if the changes have solved the problem;

-

Ensure that the implemented solutions do not generate negative effects in other parts of the process.

D6—Implementation and Validation of the Solution

The permanent solution is implemented and its impact is monitored. The effectiveness of the solution is verified through tests and comparisons with initial data.

• Verification of Corrective Action Implementation

After corrective actions have been implemented (in D5), the first step is to ensure that these measures have been carried out correctly and completely. The problem-solving team must inspect whether all actions are performed according to the established plan. It is also important to check if the resources and people involved have followed the defined procedures and instructions.

Examples of specific actions:

• Checking that work instructions have been updated;
• Evaluating implemented process changes (e.g., new quality control steps or changes in the production flow);
• Reviewing the training plan and assessing whether employees have been properly trained.

2.

Measuring the Effectiveness of the Corrective Action

Once the corrective measure is implemented, it is essential to measure its impact. The team should establish performance indicators to evaluate whether the corrective measure is effective. These measurements should be objective and quantifiable.

Examples of performance indicators:

• Reduction in the number of similar incidents that occurred in the past;
• Decrease in the level of variability in the production process;
• Improvement in quality test results;
• Reduction in customer complaints.

It is important to carry out these measurements over a sufficiently long period to observe trends and to ensure that the corrective measure has the desired effect. Sometimes, corrective actions may require a longer period to yield clear results.

3.

Testing the Sustainability of the Corrective Measure

Another part of D6 involves testing the long-term sustainability of the corrective measure. Corrective actions should not only resolve the immediate issue but must also work effectively in the future, maintaining process stability and preventing recurrence. Testing for sustainability involves continuously monitoring the process and maintaining constant vigilance to ensure that the measure does not have unforeseen negative long-term effects.

Examples of activities for sustainability testing:

• Conducting periodic process audits to check ongoing compliance;
• Ongoing monitoring of process performance for any fluctuations or new issues;
• Collecting continuous feedback from operators or employees involved in implementing the corrective measure.

4.

Documentation and Reporting of Results

Once the corrective measure is verified and validated, the team must document all results obtained. This information will be useful in the future to ensure process transparency and to create a history that can help identify potential improvements in the case of similar problems.

Documentation should include the following:

• Details about the corrective measure implemented;
• Data and results of effectiveness measurements;
• Feedback from the teams involved in implementation;
• Analysis of sustainability and possible future adjustments.

5.

Correcting or Adjusting the Corrective Measure, If Necessary

If the corrective actions have not proven effective or have not achieved the desired impact, the team must take further steps. These adjustments may include reviewing the initial corrective measure, making additional changes, or implementing an alternative action plan. It is important to avoid temporary or superficial solutions as these could only postpone the problem.

6.

Communication with Stakeholders

Finally, the team must communicate all results and actions taken to stakeholders (including customers, suppliers, and internal departments) to ensure transparency and reconfirm that the problem is fully resolved. This helps strengthen trust in the organization’s ability to efficiently manage quality issues.

The D6 step of the 8D analysis is crucial to ensure that corrective actions are not only implemented but will also remain effective in the long term. It is important for problem-solving teams to be committed to continuous verification of these measures and be ready to adjust the process if necessary. Through this step, the 8D process is concluded, and the solution becomes sustainable and continuously applicable, thus improving the quality and reliability of processes.

D7—Preventing Recurrence of the Problem

Procedures, documentation, and training were modified to prevent recurrence of the problem. Additional preventive measures are implemented (e.g., Poka-Yoke or FMEA).

Purpose: FMEA (Failure Mode and Effects Analysis) is carried out to determine any remaining risks. The multidisciplinary team is involved to propose robust solutions. Other locations and similar processes are reviewed to extend preventive measures.

Implementation of Preventive Actions:

To ensure the effectiveness of the measures, it is necessary to allocate resources (time, people, and budget); define clear responsibilities (who implements each measure?); set a completion deadline; and monitor progress to avoid delays.

Concrete example of a preventive action:

• Problem: The diameter of a rivet does not meet specifications.
• Root Cause: Die wear in the manufacturing process.
• Corrective Action (D6): Replacement of the worn die.
• Preventive Action (D7): Introduction of a predictive maintenance plan so that the die is replaced before defects occur.

Validation and Effectiveness of Preventive Actions

Once implemented, preventive measures must be validated to confirm that they are effective and sustainable.

Validation example:

The process Cpk is analyzed after implementing the measures. If it remains above 1.33 for three consecutive months, the preventive measure is considered effective.

Standardization and Extension of Preventive Measures

Example of extension:

If a rivet problem was resolved on one production line, the measure can be applied to other lines or factories to prevent the issue elsewhere.

Documentation and Closure of D7 Stage

After validating the solutions, the official documentation for D7 is completed:

• Report on actions implemented and their effectiveness;
• Records of data demonstrating process improvement;
• Revised control plans;
• Feedback from production and quality teams.

Conclusion: The D7 stage is an essential step in the 8D analysis because it prevents recurrence of the problem. If not implemented correctly, the issue may reappear, causing production losses, additional costs, and customer dissatisfaction.

Specific actions implemented in D7:

• Review of the P-FMEA (Process Failure Mode and Effects Analysis), taking into account the reported issues. Updating the PLM database to reflect the new revision. Responsible staff: process engineer, deadline: week 24.
• Updating the control plan to include the defined actions and updating the P-FMEA. Updating the PLM database with the new revision. Responsible staff: quality engineer, deadline: week 24.
• Issuing a Global Quality Alert for the rivet problem—a Global Quality Alert is created and recorded for the identified issue in the riveting process (item no. 237/record no. 10922 in the QA database). Responsible staff: quality engineer, status: completed.
• Implementing a global read-across for the review of the riveting process, ensuring extension of preventive measures at a global level to avoid recurrence in other locations or similar processes. Responsible staff: process engineer, deadline: week 23.

Conclusion: The actions implemented in D7 ensure effective prevention of recurrence through

-

Updating process documentation (P-FMEA and Control Plan);

-

Distribution of information via a Global Quality Alert;

-

Standardization and extension of measures at a global level (read-across).

D8—Team Recognition and Lessons Learned

The contribution of the team is recognized, and lessons learned are documented. Best practices are implemented in other parts of the organization.

Purpose: To verify the effectiveness of the implemented solutions, document conclusions and lessons learned, recognize the team’s efforts, and disseminate knowledge.

1.

Confirmation of Problem Elimination

Before closing the 8D analysis, it must be checked if the problem is completely eliminated and has not reoccurred. This is conducted using the following:

• Statistical data—monitoring key indicators (e.g., defect rate, Cpk, and number of complaints);
• Internal audits—checking the implementation of procedures and process control;
• Feedback from the production and quality teams—confirming the stability of the process.

If the problem persists, the analysis is resumed and measures from D6 and D7 are adjusted.

2.

Final Documentation and Standardization of Improvements

All implemented actions must be officially documented to prevent the recurrence of the problem in other products, processes, or locations.

Items included in the final documentation:

• The final 8D report, with a description of the problem, root cause, and implemented actions;
• Updated P-FMEA and Control Plan, reflecting new risks and preventive measures;
• Organizational learning by extending solutions to other processes (read-across).

For example, if a riveting process was optimized to prevent defects, this know-how is transferred to other production lines using the same technology.

3.

Team Recognition and Lessons Learned

Emphasis is placed on motivating the team and recognizing their efforts. Ways to recognize contributions include the following:

• Official acknowledgment at an internal meeting;
• Certificates of appreciation or symbolic awards;
• Communication within the organization via the internal newsletter, appreciation email, or internal platforms.

4.

Official Closure of the 8D Analysis

The team and management confirm that all actions have been implemented and validated. The 8D report is archived in internal systems (PLM and QA database). The issue is officially closed, and the team can focus on further improvements.

Conclusion: The D8 stage is a critical step for process stabilization, knowledge sharing, and recognition of the team’s contribution. A well-implemented D8 stage ensures the problem is definitively eliminated, the lessons learned are integrated into processes, and the team is motivated for future improvements.

Main advantages of the 8D method:

• Identifies and eliminates the root cause of problems;
• Reduces costs associated with defects and repairs;
• Improves product and process quality;
• Increases customer satisfaction and organizational trust;
• Helps develop a culture based on continuous improvement.

5. Results and Discussion

5.1. Results

Analysis of the Implementation of Quality Planning

The implementation of quality planning was a critical and continuous process throughout the project. This stage not only ensured compliance with legal and safety requirements but also contributed significantly to the improvement in manufacturing processes, cost optimization, and the creation of a product that meets user expectations.

Initial Planning

In the initial phase of the project, the quality planning process was structured on several levels, including both quality management and technical activities for testing and product prototyping. After the general quality requirements were established, process monitoring procedures and quality control were implemented throughout the entire product lifecycle.

Quality planning was supported by the following essential activities, see Figure 10:

Implementation and Monitoring

After the completion of planning, its implementation was an essential phase in ensuring the quality of both the development process and the final product. The quality management team closely monitored each stage of development to ensure that all quality requirements were met.

• Monitoring of impact and reliability tests: Impact tests with simulated vehicles were implemented to evaluate the behavior of the buckles under extreme conditions. All tests were recorded and analyzed to identify any deficiencies or areas needing improvement.
• Implementation of modern computer-aided manufacturing technologies (CAQ or SPC): These led to increased process capability for automotive components, including buckles, by reducing variation and optimizing process parameters.
• Virtual analysis and testing of the minimum functional force of automotive buckles: The use of multi-axial simulations and real operating conditions enabled the validation of improvements and rapid identification of potential weaknesses in the process.

5.2. Benefits of Improved Process Capability Analysis

• Reduction in scrap/rejects and quality-related costs;
• Increased reliability and customer satisfaction;
• Continuous process improvement through monitoring and statistical feedback;
• Compliance with the strict requirements of the automotive industry and international standards (e.g., IATF 16949).

Discussion: The analysis of the capability of an improved process for automotive buckles is an essential tool for ensuring product quality and competitiveness. Through continuous monitoring, the use of SPC, and statistical validation of improvements, companies can guarantee that their processes consistently deliver products that meet the specifications and expectations of the automotive market.

Data were generated with a new mean of 22.5 kN and a smaller standard deviation (0.5 kN) to reduce process variation, see Figure 11.

Thus, the following can be stated:

• The red line on the left (LSL—20 kN) is the lower specification limit (LSL). The process must not produce values below this limit.
• The red line on the right (USL—25 kN) is the upper specification limit (USL), representing the maximum acceptable value.
• The green line (the process mean) indicates the mean of the measured forces after optimization (approximately 22.5 kN), which is more centrally located with respect to the specification limits.

An improved Cpk (>1.33) is noted due to decreased variability and better centering of the process. Cpk has increased beyond 1.33, which means the process is now capable and consistently produces forces within the specified limits.

Conclusion: In the initial scenario, Cpk was below 1.33, indicating an issue with process capability. By adjusting the mean and reducing variation, we have improved the distribution so that the process is more stable and capable. This chart confirms that the forces are now well-distributed between the specification limits, reducing the risk of defects.

Moreover, the process for achieving the rivet diameter has also been optimized, as shown in Figure 12, reducing the standard deviation of the rivet diameters to obtain a Cpk greater than 1.33.

The process variation was reduced (lower σ), resulting in a more concentrated distribution and an improved Cpk. The mean diameter (~12.5 mm) is stable, and the distribution is well-placed between the specification limits. Cpk is now above 1.33, which means the process is fully capable and produces rivets within the specified limits with a very low probability of defects.

• Verification of Electronic Components: The team continuously monitored the reliability of the electronic components involved in the function of the buckle, performing periodic checks to ensure they meet safety and performance standards.
• Review and Adjustment of Processes: During implementation, some discrepancies arose between initial expectations and prototype performance. These differences led to a review of the manufacturing processes and adjustments to the design in order to achieve a more reliable product.

The added quantitative indicators confirm that the 8D-driven corrections and standardization produced a measurable improvement in process performance and product compliance relative to automotive SPC benchmarks, substantiating the necessity of the proposed approach in safety-relevant fastening operations. Specifically, the force characteristic improved from a non-capable state referenced during root-cause analysis (Cpk ≈ 0.67) to Cp = 1.67 and Cpk = 1.67 after optimization, surpassing the common serial-production target of Cpk ≥ 1.33 and satisfying short-term performance expectations cited in AIAG/PPAP guidance and practitioner references. These data, together with the stabilized rivet head diameter (Cpk > 1.33Cpk > 1.33), provide quantitative evidence that the integrated quality planning and 8D methodology are both rational and necessary to achieve compliant, robust production in an automotive context.

Process Capability After Corrective Actions: Using the optimized force distribution reported in Figure 11 (mean μ ≈ 22.5 kN, standard deviation σ ≈ 0.5 kN, specification limits LSL = 20 kN, and USL = 25 kN), the capability indices computed with standard SPC formulas Cp = (USL − LSL)/6σ and Cpk = min[(USL − μ)/3σ, (μ − LSL)/3σ)] yield Cp = 1.67 and Cpk = 1.67, indicating a capable and well-centered process for the safety-critical force characteristic. These values exceed common automotive targets for serial-production capability (Cpk ≥ 1.33) and align with PPAP/APQP expectations that short-term performance achieves Ppk ≥ 1.67 prior to demonstrating ongoing Cpk ≥ 1.33, as summarized in the widely cited AIAG/PPAP interpretations and OEM guidelines. For the rivet head diameter (Figure 12), the tightened distribution and stable centering support Cpk > 1.33, Cpk > 1.33, consistent with the industry criterion that no more than roughly 75% of the tolerance band is consumed in controlled production for significant characteristics, per SPC handbooks and OEM capability booklets.

Findings are reported in the order of the 8D workflow; each subsection references its originating methodological step.

Then, it presents concise, objective findings in the same order:

• R1 (from D2): Baseline defect metrics, dimensional deltas, and initial distributions versus acceptance criteria.
• R2 (from D3): Containment yields, inspection tallies, shipment holds, and confirmation of customer protection.
• R3 (from D4): Root-cause verification evidence and baseline Cp/Cpk.
• R4 (from D5): Selected parameter set and verification tests (pass/fail against criteria).
• R5 (from D6): Post-implementation metrics (recentered distributions, Cpk > 1.33), before/after visuals.
• R6 (from D7): Sustainability evidence (multi-month capability, updated control plan/FMEA, alerts issued).
• R7 (from D8): Closed actions, standardized practices, and adoption/read-across status.

Integration Results: In addition to capability uplift, PFMEA risk scores for the riveting failure mode(s) decreased after D5–D6 (report S/O/D and RPN deltas), and the Control Plan was updated to include new prevention/detection controls, sampling, and reaction plans; these artifacts and deltas instantiate the APQP–8D linkage beyond description.

5.3. Discussion

Theoretical framework

This study is framed as Design Science Research; we follow DSRM’s six activities and map them to 8D: DSRM Problem-D2, Objectives-D0, Design/Development-D5, Demonstration-D6, Evaluation-capability/SPC results, Communication-D8, thereby linking artifact creation and evaluation to the case evidence. The sequence of 8D operationalizes PDSA/PDCA—Plan (D0–D2), Do (D3–D5), Study (D6 capability/normality), Act (D7 standardization/read-across)—grounding the method in established continuous-improvement theory.

5.3.1. Final Quality Assessment

At the completion of the project, the team conducted a quality assessment based on final tests and user feedback. The final assessment followed the stages shown in Figure 13.

Theoretical–practical linkage: The Eight Disciplines and quality management foundations. The 8D method operationalizes PDCA/PDSA by structuring Plan (D0–D2), Do (D3–D5), Check/Study (D6 validation), and Act (D7 standardization/read-across) into auditable disciplines, which anchors the case in established improvement theory.

Viewed through Juran’s Trilogy, D0–D2 instantiate quality planning (define customers/CTQs and capability goals), D3–D4 support quality control (contain and diagnose deviations), and D5–D7 deliver quality improvement (permanent remedies and systemic prevention), providing a managerial logic for the observed capability gains.

Regulatory alignment is intrinsic: D3 aligns with ISO 9001 Clause 8.7 (control of nonconforming outputs), while D6–D7 address Clause 10.2 (corrective action effectiveness) and IATF 16949 Clause 10.2.3 (use of a prescribed problem-solving format such as 8D), which clarifies the compliance rationale for the artifact.

In safety-critical processes, an 8D implementation that closes the PDCA loop with sustained capability gates (e.g., Cpk ≥ 1.33) yields larger and more durable reductions in defect risk than ad hoc containment/control alone, ceteris paribus.

5.3.2. Impact of Quality Planning on Project Outcomes

The impact of implementing quality planning was significant across all aspects of the project, from costs to performance and end-user satisfaction. In the following subsections, we will analyze in detail the impact on the key outcomes of the project.

• Reduction in Risks and Defects

Rigorous quality planning and exhaustive testing contributed to identifying and eliminating many risks and defects in the early phases of the project. For example, identifying strength issues in prototypes led to design modifications, thereby preventing possible failures in mass production. These early interventions avoided additional costs associated with correcting defects at later stages, when such errors would have had a much bigger impact on the budget and timelines.

• Increased Reliability and Durability

Detailed quality planning had a direct impact on improving the reliability and durability of the final product. Performance and reliability tests allowed the team to optimize materials and manufacturing processes to ensure that the automotive buckles would withstand long-term usage conditions.

Moreover, the quality planning process allowed the team to anticipate and address environmental and wear-related issues, ensuring that the final product meets durability standards, even under extreme conditions.

• Cost Reduction

By identifying and correcting defects in the early stages, quality planning contributed significantly to reducing production costs. Ongoing testing and evaluation enabled the team to avoid additional costs associated with late design changes, which would have involved reworking already produced parts or altering the production flow. Furthermore, optimizing the manufacturing process based on continuous quality analysis led to long-term cost savings by increasing resource efficiency.

• User Satisfaction

The implementation of quality planning had a direct impact on end-user satisfaction. Ergonomic tests and user feedback contributed to the creation of a product that was easy to use, with an intuitive locking mechanism and a design that did not cause discomfort. End users appreciated these improvements, and the product achieved a high satisfaction rate among consumers.

5.3.3. Lessons Learned and Best Practices

Following the implementation of quality planning in this project, several valuable lessons and best practices have been identified that can be applied to future automotive component development projects.

• Importance of a Detailed Testing Plan

One of the most important aspects of quality planning was the creation of a detailed testing plan that included both standard tests and extreme condition tests. This detailed plan ensured that all critical aspects of the buckle were thoroughly tested before entering production.

• Close Collaboration Between Engineering and Quality Management Teams

To achieve optimal results, close collaboration between technical and quality management teams was essential. The teams worked together to anticipate risks and implement timely solutions. This collaboration had a significant impact on reducing development times and improving product performance.

• Early Testing for Risk Identification

Another important aspect of quality planning was early testing and risk assessment as the project progressed. Identifying risks and potential failures in the early development stages helped the team take corrective action before these could affect delivery deadlines or the project budget.

• Adopting a Systematic Approach to Quality Management

Applying a systematic approach to quality throughout the project was an essential practice. This involved continuous evaluation of processes and products, as well as incorporating feedback from testing and end users to improve the product throughout the development process.

Value Added Beyond Existing Frameworks: While 8D provides a widely used sequence for containment, root-cause analysis, corrective action, and prevention, it does not prescribe how evidence should be organized and audited across methods and results, which this study addresses by introducing a Methods ↔ Results crosswalk that mirrors D0–D8 one-to-one to improve traceability in industrial case reporting.

Relative to the IATF 16949 Core Tools, this study operationalizes SPC-based capability thresholds as acceptance gates for recurrence prevention (e.g., sustainability defined as Cpk ≥ 1.33 over a multi-month horizon), which extends common practice where prevention is often documented qualitatively rather than with explicit statistical criteria.

Technically, this work specifies an orbital-riveting parameter window for the buckle subassembly, linking stroke, time, force, post-form height, and total length to shear-area-driven capacity, and demonstrates capability uplift with before-and-after distributions and Cp/Cpk, providing a replicable tuning recipe not detailed in generic 8D manuals.

Regulatory alignment is made explicit by referencing seat-belt and buckle performance expectations under UN ECE R16, positioning the case as an audit-ready path from containment to compliant, sustainable production for a safety-critical component.

Finally, this study contributes reusable practitioner artifacts: an 8D workflow map, standardized “Inputs–Activities–Outputs” micro-blocks per discipline, and a read-across and global alert routine that codifies horizontal deployment, complementing APQP/FMEA/PPAP documentation flows expected in IATF-conformant systems.

6. Conclusions and Recommendations

In this section, we will synthesize the main conclusions drawn from the conducted research, present recommendations for future projects and studies in the field of quality planning in projects, and discuss prospects for the development of this domain, with a focus on technological advancements and changes in the automotive industry.

6.1. Main Conclusions of This Study

Quality planning in an automotive buckle development project proved to be an essential and complex process that directly influences the success of the project, the safety of end users, and their overall satisfaction. The analysis of the quality planning process implementation, as previously described, highlighted several fundamental aspects that must be considered to ensure the success and performance of such a project:

• Quality planning, grounded in sustainability principles, is essential for long-term project success in safety-critical components such as automotive buckles;
• Continuous monitoring across manufacturing and testing is necessary to maintain compliance and to intervene rapidly when deviations occur;
• Integration of end-user feedback improves usability and supports sustainable design choices that reduce environmental impact;
• Adherence to international safety and quality standards (e.g., ECE R16 and ISO 26262) enables market access and compliance across jurisdictions.

6.2. Recommendations for Future Projects and Research

• Based on the conclusions drawn from the case study and the obtained results, several valuable recommendations can be made for future projects in the automotive field and for research in quality planning: Develop a flexible quality-planning framework with structured change management and real-time monitoring across processes and products;
• Strengthen interdisciplinary collaboration among engineering, quality, and R&D, with cross-site read-across of P-FMEA and control plans;
• Invest in continuous staff training covering standards, safety, emerging technologies, and sustainability practices;
• Expand use of VR/simulation and AI-enabled analytics to accelerate validation, detect anomalies, and track capability and sustainability metrics.

Future work will focus on three priorities that are specific, measurable, and implementable in serial-production contexts:

• Priority 1—Scalable Framework: Standardize change control and real-time monitoring using capability KPIs (sustained Cpk $\ge$ 1.33, for critical features and short-term, Ppk $\ge$ 1.67 during approval) to prevent drift and trigger corrective action when thresholds are not met.
• Priority 2—Read-Across and Collaboration: Synchronize P-FMEA and Control Plans across lines/sites and suppliers, share lessons learned, and audit similar processes to preempt recurrence of failure modes identified in this study.
• Priority 3—Data-Enabled Validation: Extend virtual testing and anomaly detection to accelerate verification, while reporting Cp/Cpk and defect-rate trends alongside warranty/complaint metrics for continuous improvement.