Search Results (45)

Reverse logistics lacks an exhaustive study on its impact on supply chain management and its integration with Continuous Improvement. Through a survey submitted to companies in the northern region of Portugal, this study shows how reverse logistics and Continuous Improvement have been considered and applied by companies. Microsoft Forms was used to properly administer the survey, which was submitted to 80 companies to collect data from a convenience sample. Yet, it was only possible to validate 60 responses, which, for a confidence level of 90%, represents a margin of error of 10.62%. Regarding the data analysis, descriptive statistics was used to present the main results. Nonetheless, normality tests were also carried out to understand if parametric or non-parametric methods could be applied to analyze the number of weekly hours dedicated to the reverse logistics process. The results show that most companies have informal reverse logistic management, being the biggest companies or those with higher turnover who apply a formal process. The main activity performed in the reverse logistics process is resale and remanufacture. For the interviewed companies, the main reason for having a reverse logistics process is to reduce materials’ or products’ costs and simultaneously increase profits by reusing products or materials. Regarding the factors that impact the performance of RL systems, the non-uniformity of the returned product is the most demandable. The most widely used continuous improvement tools in reverse logistics are 5S and the Kaizen. In sum, despite the benefits of improving customer satisfaction, reverse logistics should also be considered in enhancing sustainability and complying with regulations. Full article

Background/Objectives: Healthcare systems face persistent challenges in improving efficiency, optimizing resources, and delivering high-quality care. Traditional continuous improvement methodologies often rely on subjective assessments, while data-driven approaches typically lack human-centered adaptability. This study aims to develop an integrated framework combining Kaizen principles with Process Mining capabilities to address these limitations in healthcare process optimization. Methods: This research employed a structured literature review approach to identify key concepts, methodologies, and applications of both Kaizen and Process Mining in healthcare settings. The study synthesized insights from the peer-reviewed literature published in the last two decades to develop a conceptual framework integrating these approaches for healthcare process improvement. Results: The proposed framework combines Kaizen’s employee-driven approach to eliminating inefficiencies with Process Mining’s ability to analyze workflow data and identify process deviations. The integration is structured into four key phases: data collection, process analysis, Kaizen events, and continuous monitoring. This structure creates a feedback loop where data-driven insights inform collaborative problem-solving, resulting in sustained improvements validated through objective process analysis. Conclusions: The integration of Kaizen and Process Mining offers a promising approach to enhancing workflow efficiency, reducing operational errors, and improving resource utilization in healthcare settings. While challenges such as data quality concerns, resource constraints, and potential resistance to change must be addressed, the framework provides a foundation for more effective process optimization. Future research should focus on empirical validation, AI-enhanced analytics, and assessing adaptability across diverse healthcare contexts. Full article

Fiercer competition across all industries has made identifying and eliminating lean wastes to enhance sustainability performance an effective route that many companies take. This study focuses on the production process of wood park/garden benches at a company that manufactures outdoor wood furniture. The goal was to identify lean wastes within a sustainability framework across seven operations and integrate multi-criteria decision making (MCDM) methodologies for waste elimination. Eleven lean KPIs addressing economic and environmental sustainability were used to develop and prioritize 13 lean failure modes (LFMs) with Risk Priority Numbers (RPNs) above 100, leading to lean project proposals for each LFM. Eighteen lean tools were ranked using the Fuzzy Quality Function Deployment (Fuzzy QFD) method. A total of eight improvement propositions, namely, Kaizen and continuous improvement, upgrade machinery for energy efficiency, Just-In-Time (JIT), optimize production processes with lean methodologies, implement cost reduction strategies, Total Productive Maintenance (TPM), Investing in Automation, and Andon were implemented. Significant improvements were observed post-implementation: total lead time was reduced by approximately 38.46%, value-added time by 22.05%, and non-value-added time by 47.64%. The required number of workers decreased by 14.29%, and the total inventory decreased by approximately 57.31%. The results contribute to sustainability goals by reducing energy consumption and waste while increasing economic efficiency. It also provides a robust framework for decision making in fuzzy environments, guiding practitioners and academics in lean management and sustainability. Full article

Background: The integration of lean management and Industry 4.0 offers great potential for improving the efficiency and effectiveness of production. However, there is still minimal empirical research on how these two approaches interact in practice, including possible synergies and conflicts. In this paper, we use empirical observations to examine how and why Industry 4.0 technologies can support and enhance the continuous improvement process, a fundamental aspect of lean management. We discuss how these technologies specifically contribute to continuous improvement and their overall impact on operational efficiency. Methods: Our research drew on five case studies, capturing the firsthand experiences of industry professionals—specifically, digitization managers and production managers from manufacturing companies across Europe. We analyzed data using qualitative content analysis, applying a structured approach of coding, summarizing, and cross-case comparison to identify key patterns and insights. Conclusions: Our study has shown that digitalization can contribute to an advanced continuous improvement process in several ways. Through a literature review as well as the analysis of use cases, we were able to develop a new model that describes how I4.0 technologies improve the continuous improvement process, a key lean principle. The model highlights five key areas of impacts: increasing flexibility, transparency, and reliability, as well as improved decision-making and acceptance of change processes. Full article

The Clay N. Hixson Student Success Center within the College of Engineering at Tennessee Tech University has undergone a transformative upgrade by integrating the Define, Measure, Analyze, Improve, and Control (DMAIC) framework with select Kaizen principles for continuous improvement to enhance student support services. Key performance indicators (KPIs) have been employed to assess the achievement of core goals, significantly advancing recruitment, retention, and overall student success. Implementing the DMAIC framework has streamlined processes such as a unified degree map and a math bridge program, resulting in a 53% increase in incoming first-year students and broadening the College of Engineering’s outreach. These efforts have also contributed to a 10% increase in first-to-second-year retention rates. Through the utilization of DMAIC, the regular redistribution of advisor caseloads and cross-training has been facilitated, ensuring timely student support without overburdening advisors. Additionally, targeted academic support initiatives have reduced the at-risk student population from 19% to 11%. These management techniques extend to multiple initiatives, including enhancements to high school summer camps, advisor listening sessions, and student surveys designed to meet evolving student needs. Creating specialized areas for academic advisors has also supported their professional growth, contributing to better student outcomes. This paper comprehensively analyzes these strategies and provides valuable insights for institutions seeking to apply DMAIC and continuous improvement models to strengthen student support systems. Full article

Background/Objectives: The implementation of information quality value stream maps (IQ-VSMs) in food animal production systems can increase our understanding of the opportunities and challenges when using laboratory testing for antimicrobial resistance (AMR) to support antimicrobial stewardship (AMS). Our objectives were to (1) explore the implementation of information quality value stream mapping as a continuous improvement tool to inform decisions for bovine respiratory disease (BRD) management and AMS and (2) apply the information quality dimensions to identified Kaizen opportunities for the integration of laboratory data into BRD management systems to assess the appropriateness of BRD treatment plans in western Canadian feedlot production. Methods: A ‘Current State’ IQ-VSM outlined the processes, available information, information processing steps, and control decisions contributing to BRD management and treatment in commercial western Canadian feedlots, recognizing that laboratory BRD pathogens and AMR data are typically not part of BRD management. Results: The ‘Future State’ IQ-VSM incorporated Kaizen opportunities for improvement, including (i) the strategic collection of respiratory samples from representative samples of calves for laboratory analysis, regardless of clinical BRD status, (ii) compilation of laboratory data at the pen and feedlot levels, and (iii) analysis of pen- and feedlot-level laboratory data to inform the veterinarian’s assessment of the appropriateness of current BRD treatment plans. Conclusions: The IQ-VSMs provided a valuable framework to visualize the integration of BRD pathogen and AMR laboratory data to support AMS and address any potential future testing requirements. Full article

The US manufacturing sector faces critical challenges: improving sustainability, reducing energy consumption, and reducing greenhouse gas emissions. Energy Treasure Hunt (ETH) training, a service provided by the US Department of Energy’s Better Plants program, offers a compelling solution. Although ETHs have traditionally focused on energy and cost savings, data indicate that ETHs can be used to identify opportunities to reduce emissions and water use and to support a sustainable and circular operation. These 3-day on-site events engage employees in a collaborative search for operational and maintenance efficiency improvement opportunities. The success of ETHs lies in a comprehensive methodology. Each phase in an ETH uses various tools and resources to empower employees to identify practical solutions. This study presents data from 13 ETHs conducted between 2023 and 2024 across diverse manufacturing subsectors in the United States and demonstrates that the events can help create a pragmatic decarbonization pathway. Through the events, a total of 234 energy and emissions reduction opportunities were identified, and the potential impact is significant. Implementing the recommendations could translate to annual savings of 497,299 MMBtu of energy, 64,374 kgal of water, and 4.85 million tCO₂e of emissions. The fiscal savings from the proposed recommendations translate into nearly $5 million annually. This study identifies the opportunities by energy system type and by the specific actions recommended, while also analyzing the identified opportunities, presenting the most established sustainability recommendations. Case studies from participating partners are presented to further demonstrate that ETHs provide a practical and impactful approach to reducing energy consumption, emissions, and operating costs and promote a more sustainable future for the industrial sector. Full article

Due to the context of market competitiveness and the economic and financial crisis, companies need to optimize their production systems, tracking the raw material from the suppliers until the final product arrives to the consumer. The Lean philosophy assumes a relevant role for today’s industries through its concepts and tools, enabling optimization, increasing revenues, and having the principle of not expropriating the environment. This article aims to analyse the level of maturity reached by industries in Luanda regarding the practices and tools of the Lean philosophy. A Lean graphic model was built, measured by the Lean Enterprise Self-Assessment Tool (LESAT) maturity model through qualitative and quantitative research focusing on the statistics of 87 circumscribed industries at Viana Industrial Development Pole in the Economic Special Zone of Luanda region, Angola. Initially was conducted an analysis to see whether Lean practices and tools were used: 5S, OKJust-In-Time, Kanban, Bottleneck Analysis, Jidoka, Kaizen, Poka-Yoke, SMED, Gemba, Heijunka, Value Stream Mapping, Hoshin Kanri, and Andon. The next steps were to analyse the following: customer value analysis; value chain analysis; analysis of the use of the pulled production system; and analysis of the use of the continuous production flow analysis of continuous improvement. The result shows these industries using the Lean philosophy at a very low level of maturity. Only the 5S tool was known and used. The JIT, Kanban, and Bottleneck Analysis were moderately used. Only 50% of Lean practices were used. Full article

Total quality management (TQM) is a strategic philosophy that has adopted kaizen activities which drives the business to carry out activities effectively to yield the best desired output, hence, a profitable organization. The kaizen philosophy acts as a catalyst in productivity rate and integrated management systems (IMS) which results in drastic improvements. When the nonconformity arises within the process, the accuracy of the problem solving determines quality of preventive action, therefore the preventive action should be accompanied by the opportunity of improvement from the raised nonconformance. This research seeks to add more knowledge and upgrade technology of problem-solving models relating to the integrated management systems by examining various troubleshooting models for problem solving and preventive action related to quality nonconformances, safety incidents and engineering breakdowns. Hence, the aim of this research is for troubleshooting model technique enhancement for issues related to process engineering, quality management systems and occupational health and safety by creating a model which analyses kaizen projects from the corrective and preventive action analysis of nonconformances. The proposed troubleshooting model was developed using lean techniques and risk rating tools; it was then applied to the case study company for simulation and the outcomes resulted in the closure of nonconformances and continual improvement of future projects. The proposed model is more advantageous to the manufacturing industries seeking to improve their Corrective Action and Preventive Action (CAPA) systems. Full article

The Occupational Health and Safety system enforces the continual improvement culture in industries for much safer processes and zero injuries. The Quality Management System also enforces the same philosophy of continual improvement within the processing system for zero defects, hence a high productivity rate. Good quality products always result from good Overall Equipment Effectiveness; hence, Process Re-Engineering is essential for the good functioning of machinery. This research is based on Integrated Management System requirements in terms of problem-solving, especially the opportunities that arise within Quality nonconformances, Safety Incidents, as well as Process Engineering related breakdowns. This study aims to develop a troubleshooting system that evaluates continual improvement projects. The method used to develop the troubleshooting system is based on Total Quality Management, where lean principles are combined with kaizen concepts and quality standards. The proposed troubleshooting system is separated into three development phases: the first phase is for recording the details of the fault that has been raised, where one will record full details of the nonconformance, the time and date, validation of the nonconformance by the lab test or any other form of validation depending on the nature of the problem as well as the details of the location of the problem. The second phase is for problem classification, whether it is a quality nonconformance, Safety incident, or engineering-related breakdown. The deeper root cause analysis is performed by an application of lean techniques, which are the eight types of waste, Five Whys and Ishikawa analysis. The eight types of waste identify the type of waste contributed by the problem, the Five Whys analysis assists in finding the reason for the problem occurrence, and the Ishikawa analysis classifies the problem accordingly, which assists the analyst in identifying the area to focus on for problem-solving. The third phase is for a database system and an application of the kaizen philosophy by evaluating continual improvement projects as well as status reports on the permanent solutions to the faults. The proposed troubleshooting model was applied in a case study company to upgrade the problem-solving model that the company was using which was assisting for corrective and preventive action. The study resulted in drastic improvements; hence, continual improvement projects were evaluated within the problem occurrences. Full article

To survive in highly competitive markets, industries focus on enhancing product quality and customer satisfaction. One specific iteration of this approach sees industries striving to optimize processes to improve product quality while generating minimum waste. This has encouraged companies to begin adopting management practices such as lean six sigma (LSS) and kaizen alongside their implementation of digital technologies of automating processing. This study aims to identify and analyze the barriers to integrating LSS practices with Industry 4.0 technologies for small and medium enterprises. Upon shortlisting fifteen barriers from an exhaustive literature review, the Grey-Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology is used to analyze those shortlisted barriers and establish causal relations between barriers and outcomes. The findings identify the lack of available infrastructure, lack of training on LSS, and lack of consultants in the field as the most dominant barriers in the cause group. Furthermore, the influence map of barriers produced demonstrates the relationship between cause-and-effect barriers. This study’s findings will ensure that small and medium enterprises formulate business strategies that mitigate the barriers to integrating LSS with Industry 4.0. This study offers insights into overcoming the identified challenges by proposing strategies to enhance product quality and the accuracy of enterprise decision-making, thereby facilitating a successful integration and fostering sustainable growth in SMEs. Full article

Research in lean production has recently focused on linking lean production to Industry 4.0 by discussing the positive relationship between them. In the context of Industry 4.0, data science plays a fundamental role, and operations management research is dedicating particular attention to this field. However, the literature on the empirical implementation of data science to lean production is still under-investigated and details are lacking in most of the reported contributions. In this study, multiple case studies were conducted involving the Italian manufacturing sector to collect evidence of the application of data science to support lean production and to understand it. The results provide empirical proof of the link and examples of a variety of data science techniques and tools that can be combined to support lean production practices. The findings offer insights into the applications of the traditional lean plan–do–check–act cycle, supporting feedback on performance metrics, total productive maintenance, total quality management, statistical process control, root cause analysis for problem-solving, visual management, and Kaizen. Full article

Furniture production is a specific industrial sector with a high human labor demand, a wide range of materials processed, and short production runs caused by high customization of end products. The difficulty of measuring the aesthetic requirements of customers is also specific to furniture. This review of academic papers identifies and explains effective quality management strategies in furniture production. The reviewed literature highlights a range of quality management methodologies, including concurrent engineering (CE), total quality management (TQM), lean manufacturing, lean six sigma, and kaizen. These strategies encompass a variety of pro-quality tools, such as 5S, statistical process control (SPC), quality function deployment (QFD), and failure mode and effects analysis (FMEA). The strengths of these quality management strategies lie in their ability to enhance efficiency, reduce waste, increase product diversity, and improve product quality. However, the weaknesses concern implementation challenges and the need for culture change within organizations. Successful quality management in furniture production requires tailoring strategies to the specific context of the furniture production industry. Additionally, the importance of sustainability in the furniture industry is emphasized, which entails incorporating circular economy principles and resource-efficient practices. The most important finding from the literature analysis is that early detection and correction of poor quality yields the most beneficial outcomes for the manufacturer. Therefore, it is essential to strengthen the rigor of quality testing and analysis during the early stages of product development. Consequently, a deep understanding of consumer perspectives on required furniture quality is crucial. The review identified two research gaps: (1) the impact of unnecessary product over-quality on the efficiency of furniture production and (2) the influence of replacing CAD drawings with a model-based definition (MBD) format on quality management in furniture production. Full article

Health Improvement Through Employee Control (HITEC) is a 16-year program directed toward the health of corrections personnel and developed through the application of the principles of Participatory Action Research (PAR) and participatory ergonomics. Its impetus has always been the adverse health status of the corrections workforce: early mortality, depression, obesity, and hypertension. The HITEC program trained small “Design Teams” (DTs) of front-line personnel in participatory methods for intervention design for health improvement and organizational change in line with the Total Worker Health^® principles. Periodic surveys and physical testing were introduced for longitudinal assessments. Comparative interventions at comparable sites included DTs without a priori assignation, problem-focused kaizen effectiveness teams (KETs), and bargaining unit-centered DTs. DT resilience and the replacement of members who transferred facilities or retired was aided by novel cooperative administrative structures. DT-generated interventions included stress lounges, changes in critical event report writing, a joint program with trained inmates to improve air quality, and training in staff mental health and sleep behavior. A specialized peer-to-peer Health Mentoring Program (HMP) paired new officers with trained peers. Many interventions and program features were institutionalized, thus improving prospects for self-supporting program longevity. Participatory interventions designed and supported by the corrections workforce were found to be both feasible and exceptionally effective. Full article