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Applying the Plan-Do-Check-Act (PDCA) Cycle to Reduce the Defects in the Manufacturing Industry. A Case Study

Arturo Realyvásquez-Vargas
Karina Cecilia Arredondo-Soto
Teresa Carrillo-Gutiérrez
2 and
Gustavo Ravelo
Department of Industrial Engineering, Tecnológico Nacional de México/Instituto Tecnológico de Tijuana, Calzada del Tecnológico S/N, Tijuana, Baja California 22414, Mexico
Chemical Sciences and Engineering Faculty, Universidad Autónoma de Baja California, Calzada Universidad #14418, Parque Industrial Internacional, Tijuana, Baja California 22390, Mexico
Author to whom correspondence should be addressed.
Appl. Sci. 2018, 8(11), 2181;
Submission received: 16 October 2018 / Revised: 2 November 2018 / Accepted: 5 November 2018 / Published: 7 November 2018
(This article belongs to the Special Issue Applied Engineering to Lean Manufacturing Production Systems)



Featured Application

The tool of PDCA cycle, supported by other graphical tools, such as Pareto charts and flowchart, can be applied in the manufacturing industry to delete or reduce occurrence of defects.


Defects are considered as one of the wastes in manufacturing systems that negatively affect the delivery times, cost and quality of products leading to manufacturing companies facing a critical situation with the customers and to not comply with the IPC-A-610E standard for the acceptability of electronic components. This is the case is a manufacturing company located in Tijuana, Mexico. Due to an increasing demand on the products manufactured by this company, several defects have been detected in the welding process of electronic boards, as well as in the components named Thru-Holes. It is for this reason that this paper presents a lean manufacturing application case study. The objective of this research is to reduce at least 20% the defects that are generated during the welding process. In addition, it is intended to increase 20% the capacity of three double production lines where electronic boards are processed. As method, the Plan-Do-Check-Act (PDCA) cycle, is applied. The Pareto charts and the flowchart are used as support tools. As results, defects decreased 65%, 79%, and 77% in three analyzed product models. As conclusion, the PDCA cycle, the Pareto charts, and the flowchart are excellent quality tools that help to decrease the number of defective components.

1. Introduction

Lean manufacturing is a philosophy that is applied to production systems [1,2,3]. This philosophy was developed in the Toyota Production System and rapidly it was stablished in the manufacturing industry around the world [4]. According to Botti et al. [4], the main features of lean manufacturing include just-in-time practices, work-in-progress, and wastes reduction [1,2,3], improvement strategies, defects-free production, and work standardization. The main goal of lean manufacturing is increasing the company’s profits and adding value by deleting the wastes. It is by this reason that when companies seek improve the effectiveness and efficiency of their production process, they implement lean manufacturing [5,6]. Regarding the wastes, literature mentions that in the manufacturing industry they are classified into seven categories: overproduction, inventory, transport, waiting times, movements, over processing, and defects [7]. All of these wastes negatively affect the delivery times, cost, and quality of products [4,8]. In the specific case of defects, several authors point out that defects are the main cause of damages in more advanced components [9,10,11,12]. Manufacturing companies transform the raw materials or components they receive from their providers, assembling them to obtain a finished product, which must be delivered to the customer at time and without defects [13]. However, even today, defective products and components are present in the manufacturing industry, and this is a critical situation that companies in this sector are facing. Even after proper care in the design, materials selection and product manufacturing, there are defective parts [14].
This is the case of a manufacturing company located in Tijuana, Mexico. In its manufacturing processes, this company use electronic boards, which must go through a welding process. This process is carried out in the Manual Finish area, and it begins with the placement of Thru-Holes components on the electronic boards. Next, this assembly (Thru-Holes and electronic boards) is placed on a fixture to weld the components in the wave soldering machine. After this, the assembly goes to the workstation of quality inspection, where the quality worker that is responsible for checking the assembly does not have welding defects. Finally, once the assembly approves the quality inspection, it is sent to another production line, where more components will be placed on it. However, and due to the increasing demand on the products manufactured by the company, several defects have been detected in the welding process of electronic boards, as well as in the components named Thru-Holes. Among the defects that have been detected there are solder bridge, missing components, damaged component, lifted component, insufficient solder, and excessive solder. Therefore, all electronic boards that were released as products ready to be used are causing assembly and electronic test problems. Moreover, it is more difficult, and has a high cost, the fact of correcting all defects when electronic boards are already assembled with more final product components. This manufacturing company intends to comply with the requirements that were established by the IPC-A-610E standard for electronic components (see Section 3.1). It is for all these reasons that this project aims to reduce at least 20% of the defects generated during the welding process in the Manual Finish area. In addition, it is intended to increase 20% the capacity of 3 double production lines where electronic boards are processed.
To reduce or delete the wastes, such as defects, in a manufacturing company, lean manufacturing provides 25 methods, techniques, or tools [15]. Some of them are 5S, just-in-time, Kaizen, and Plan-Do-Check-Act (PDCA) cycle. In the present project only the PDCA cycle is used.
The rest of the document is organized as follows. Section 2 offers a recent literature review on the PDCA cycle and the supporting tools applied, it means: Pareto charts and flowchart. Section 3 describes the case study, the context research, and the methodology applied. Section 4 presents the results that were obtained once the methodology was applied. Finally, Section 5 contains the conclusions and recommendations derived from the case study.

2. Research Design

The problem to be solved focuses on the welding defects in electronic boards and their components. These defects were detected in the points of use, which implies that the electronic plates were released as a compliant product, but are causing problems at the time of assembly and when performing the electrical tests. Therefore, it is necessary to know the causes of the defects originated in this productive area. It is of interest to know the main defects presented, and which electronic boards models are those of greater demand to focus on these. Hence, the objective of the project is to increase the quality by reducing the defects that are generated in the welding process in models with high volume of production.
The methodology followed was based on [16] to develop the case and includes: (a) literature review from similar published articles with case studies applying the PDCA cycle, the standard related to the process, the PDCA phases, as well as the Pareto chart and flowchart tools; (b) the case study development; (c) the analyses of results; and finally, (d) the conclusions and recommendations.

3. Literature Review

A literature review was conducted to analyze the standard to acceptability of electronic assemblies; and different case studies applying PDCA cycle, which has got a diversity of applications, either for continuous improvement; when starting a new project; when developing a new or improved design of a process; when defining a repetitive work process; and, when implementing any change [17,18,19,20,21]; as well as Pareto chart and Flowchart.

3.1. IPC-A-610E Standard to Acceptability of Electronic Assemblies

Accepted in all the world as the key manufacturing standards for the industries of manufacture of printed boards and electronic products, the IPC standards are related to most of the development cycle stages of electronic products. From the design and the purchase to the assembly and packaging, the IPC standards help to guarantee a better quality, reliability, and consistence on the electronic assemblies that are part of an electronic product. Among the IPC standards are the following: IPC-A-630, IPC-A-600, IPC-4101, IPC-A-610E, and others. All IPC standards are accredited by the American National Standards Institute (ANSI).
With regard to the standard IPC-A-610E, it is a collection of visual quality acceptability requirements for electronic assemblies. In this standard, quality acceptability criteria are not focused on definite processes to perform assembly operations or authorize the repairing/modification or change of final product. In the specific case of the components named Thru Holes, the quality acceptability criteria of welding are the following:
  • There are no cavities or imperfections on the surface.
  • The terminal and the track have good wet conditions.
  • The terminal is discernible.
  • There is a 100% welding filament around the terminal.
  • The solder covers the terminal and forms a smooth finish with thin edges on the conductor tracks.
  • There is no evidence of raised filament.
In this way, all electronic components that go through a welding process must meet these criteria [22].

3.2. PDCA Cycle

The PDCA cycle, also known as Deming cycle or Shewhart cycle [23], is a lean manufacturing methodology that was developed in 1930, when there was no more exclusive products and a more quality management focusing on competitiveness raised in the global market [24,25]. According to several authors, the creator of the original PDCA cycle was an American statistician named Walter A. Shewhart [25,26]. However, William Edward Deming was who, in the 1950s, developed this method, which, today, is one of the most worldwide known and applied. In its beginnings, the PDCA cycle was used as a tool for the quality control of products [25,27]. However, rapidly, it was highlighted as a method that allowed developing improvements in process at organizational level [25,27,28]. Currently, the PDCA cycle is characterized by its continuous improvement approach [29] and it is recognized as a logic program that allows improving the activities [27,30].
Several authors state that the PDCA cycle is much more than a simple lean manufacturing tool. Instead, they mention that the PDCA cycle is a philosophy of continuous processes improvement introduced in the organizational culture of companies [20] that is focused in the continuous learning and the knowledge creation [27,31]. The following rows describe the four stages of the PDCA cycle [32]:
  • Plan: In this phase improvements opportunities are identified, and later priorities are assigned to them. Likewise, the current situation of the process to be analyzed is defined by means of consistent data, the problem causes are determined, and possible solutions are proposed to solve it.
  • Do: In this phase, it is intended to implement the action plan, select and document the information. Also, unexpected events, learned lessons and the acquired knowledge must be considered.
  • Check: In this step, the results of the actions implemented in the before step are analyzed. A before-and-after comparison is performed verifying whether there were improvements and if the stablished objectives were achieved. To this, several graphic support tools, such as Pareto chart or Ishikawa diagram, can be used.
  • Act: This phase consists in developing methods aimed to standardize the improvements (in the case objectives had been reached). In addition, the proof is repeated to obtain new data and re-test the improvement (only if data are insufficient or circumstances had changed), or the project is abandoned and a new one is begun from the first stage (in the case the implemented actions did not yield effective improvements).
To perform these steps in an effective manner, other quality tools can be required to be used. These quality tools can help mainly to analyze the problem and define the actions to be implemented [25]. According to several authors [25,33], among the quality tools most used by the companies, and that serve as support to the PDCA cycle, are the 5S, Failure Mode Analysis and Effects (FMEA), 5W1H o 5W2H, brainstorming, benchmarking; statistical process control (SPC), checklists, Ishikawa diagrams and the Pareto chart, Quality Function Deployment (QFD), the flowchart, histograms, Single Minute Exchange of Die (SMED), Poka Yoke, Servqual, times quality, and Six Sigma. In this project the graphical tools of Pareto chart and the flowchart are used.
Literature shows that different applications of PDCA cycle have been implemented with positive results achieving the reduction of costs and defects, as well as improving the quality of process and products. In this regard, Hailu, Mengstu, and Hailu [16] developed an integrated literature based Total Productive Maintenance (TPM), Toyota Production System (TPS), and Total Quality Management (TQM) model through PDCA cycle, and implementation guideline for the application of the model. Previous very few studies of uniqueness, common practices, and implementation guideline of the three systems are preserved. The findings of this research, an integrated cutting-edge model of TPM, TPS, and TQM practices and implementation guidelines are developed. The originality/value of the developed model and implementation guideline enable manufacturing industries to be continuously competitive and profitable. Likewise, Pinto and Mendes [34] investigated how environmental improvements can be achieved through operational practices of Lean Manufacturing. The adopted research method consisted of a single case study, by providing greater depth and detail of the study. As a result of the study, it was found that there was evidence for the existence of relationship between the practices of Lean (including: Kaizen, PDCA, Ishikawa Diagram, Poka-Yoke, and Standardized Work), with the reduction of environmental impacts of an organization. The application of these practices resulted in the reduction of energy consumption and water consumption. The study presented, in detail, the application of operational practices of Lean Manufacturing, with an effective view to reducing the environmental impact and cost reduction.
From a systemic perspective Luo, Li and Li [35] analyzed the feasibility of integrated management system, and then classifies the integration methods of integrated management system from different perspectives, namely, from the system level and the operational level. It analyzes the application and the advantages or disadvantages of a variety of integrated methods, indicating that the more common situation at present is taking quality management system as the center to integrate. So, they use the large-scale system integration thinking, that is, establish the management system based on PDCA, classify the links and elements of the organization according to the four sections of PDCA from the whole, large-scale system perspective, and then analyze and distinguish the elements to request and edit documents. Shahar and Salleh [36] used the methodology of PDCA, observation, conceptual generation through PUGH method, and design software (CATIA) to analyze the grinding process for producing cutting tools. The aim of this research was to develop a carbide sludge remover machine that fits perfectly into ABC Cutting Tool Industries production line. Since carbide sludge will be filtered in the filter machine, a monthly maintenance was necessary for the filter machine that included transferring accumulated carbide sludge into the waste barrel. The process of removing carbide sludge from the filter machine required two to three person and took a considerate amount of time. This research contributed to the cost reduction for the carbide sludge removal process over time and also improved the safety of the operator.
Rosa, Silva, and Ferreira [37] conducted a study developed in order to improve the assembly lines of the steel wire-ropes used to control some of the basic functions in cars, such as the elevation of car-door windows and so on. By applying Lean and PDCA methodologies that are based on an action plan, it was possible to ensure the implementation of some of the developed solutions, as well as the subsequent processes, and the registration of these as a record for the future. The performance of efficiency was dramatically increased by this study. Nabiilah, Hamedon, and Faiz [38,39] utilized the PDCA cycle approach to reduce the defects in the electrodeposition process in two phases. In the first phase, a systematic quality improvement plan and optimization were performed. The application of the PDCA cycle improved 65% of bits and reduced 34% of sanding man hour. In the second phase, the implementation of filtration system, magnetic separation, and surface adjustment process improved 36% of bits and reduced 42% of sanding man hour. Regarding the services sector, Chen and Zhao [40] applied PDCA cycle in a hospital in the Herceptin usage management application. The differences of defects rates of Herceptin management in the breast cancer patients before and after PDCA circulation method were compared. They concluded that the PDCA cycle management method could significantly reduce the defect rate of Herceptin management and ensure the drug safety of Herceptin in breast cancer patients. Tahiduzzaman et al. [41] worked in a project to reduce the defects to minimize the rework rate; identifying sewing defects for a particular product (knit T-Shirts). Pareto analysis was performed to identify top defect positions from all the defects and seven are identified where 80% defects occur, which should be the major concerning areas to minimize defects percentage. Cause-effect diagrams were constructed to show the root cause, effect, and 5S & PDCA was used to minimize the defects effectively.
Simialrly, Jagusiak-Kocik [42] presented a case study of the practical use of PDCA-cycle in a manufacturing company as a solution to quality problems that occurred during production of photo frames (discolorations and scorches on the surface of the frame). The number of non- conformant material decreased more than 60%. Kholif et al. [43] implemented PDCA cycle as a method for the continuous quality improvement in the dairy laboratories. Results showed a reduction in the number of the contaminated UHT milk samples from initial 368 to 85. Moreover, the capability index (CP) increased from 0.52 to 1.07. These reductions in the number of contaminated milk samples and increase in CP increased the efficiency from 68.02% to 74.06% and the effectiveness from 88.95% to 96.85%. Thus, PDCA methodology was successfully applied to reduce the occurrence of errors and increase the processes capability to enhance the efficiency and effectiveness of dairy laboratory. Likewise, Wazed and Shamsuddin [44] presented a systematic approach and application of the basic and advanced management tools and techniques that are used to solve the part rejection problems in a plastic moulding manufacturing plant. In order to illustrate this, their study focused on joint application of PDCA and 5S approaches. However, implementation of the joint approach results significant improvement and good impressions to the customers and a cleaner and comfortable working condition for the employees and management. Their research provides approaches to aid in reducing the online rejection during the moulding process.
Based on the successful results that were obtained in all these case studies, we decided to apply the PDCA cycle to delete or decrease the number of defects in the welding process of the Manual Finish area.

3.3. Pareto Chart

The Pareto chart is a special type of bars chart in which each bar represents a different category or part of a problem [45]. It raised when the Italian scientist named Wilfredo Pareto found that 80% of the wealth was received by 20% of people in Italy [46]. This type of chart illustrates the distribution frequency of descriptive data classified in categories. These categories are placed on the horizontal axe and the frequencies on the vertical axe [45,46]. Talking on categories, they must be in descendent order from left to right, whereas the accumulated percentage of frequencies is represented by a line. The highest bars represent the most contributing categories to the problem. Pareto charts help identify how much some specific factors influence on a problem in relation with other factors, i.e., Pareto charts help to identify the best improvement opportunities [47]. Pareto chart has the following advantages [45,48]:
  • It decomposes a problem into categories or factors.
  • It identifies the key categories that contribute the most to a specific problem; this means, prioritize the vital problems over the trivial ones.
  • It shows where to focus efforts.
Literature presents successful case studies applying pareto char. For instance, Visveshwar et al. [49] applied the Pareto chart, because it is cost effective when compared to any other complex decision-making support systems. These authors provide an organized and systematic implementation of this tool in a plastic based production industry to achieve the continuous improvement cycle. Additionally, Shailee et al. [50] and Chokkalingam et al. [51] applied Pareto chart in the identification of major defect sand inclusion in castings The Pareto chart assisted them to check and determine defect priority. As a result, it was possible to eliminate some casting defects as shrinkage. In a parallel way they applied flowchart. Similarly, Sharma and Suri [52] applied Pareto chart in production process to reducing the rejection and rework by identifying where highest rejection occurs at and to give suggestions for improvement. Finally, Nabiilah et al. [53] applied the pareto chart in an electrodeposition process to detect the most frequent defects in such a process. As result, they detected that bits were the most frequent defect in electrodeposition process.
As in the case studies of PDCA cycle, literature review shows that the Pareto chart is a useful tool to detect the most frequent defects in a process or product. Therefore, we selected the Pareto chart to detect the most frequent defects in the welding process of the manual Finish area.

3.4. Flowchart

A flowchart is a visual tool that shows the workflow for a specific work process, facilitating the understanding, standardization and improvement of such process. More precisely, a flowchart is a picture that contains the steps of a work process. It uses different symbols to represent different types of activities of a process. For instance, it uses boxes or rectangles to represent the activities or steps of the process or task, ovals, or circles to indicate the beginning and the end of the process, diamonds to indicate that decision must be made, as well as arrows to indicate the sequence of said steps. The flowchart provides the following advantages [47,54]:
  • It allows identify the sequence of necessary steps to perform a task.
  • It allows identifying the relationships among the steps.
  • It highlights the transferences, i.e., the places from where the process flows from a person to another one.
  • It allows for detecting problems in the analyzed work process.
Although the necessary steps to perform a task can be identified by means of a list, a flowchart is easier to interpret, follow, and remember. Moreover, a flowchart allows identify the process to be analyzed, the total steps in the process, and the beginning and the end of the process [54].

4. Case Study

Following subsection describes the methodology applied in the present case study.

4.1. Methodology

The PDCA cycle was used to perform the present project. As mentioned above, the PDCA cycle comprises four phases: (1) Plan, (2) Do, (3) Check, and (4) Act. Following subsections describe how each PDCA phase was applied in this project.

4.1.1. Phase 1. Plan

In this phase, the current situation of the wave welding process in the Manual Finish area was identified. To do this, a flowchart and a layout of the Manual Finish area were developed. Later, data on the number of defects in the last five months were obtained by means of the Flight Control platform of the company. Figure 1 shows the Flight Control platform screen. Once the defects that are presented in the Manual Finish area were known, the next step was to find those that have occurred in higher amount. This step was done by means of a Pareto chart. Finally, the defects were saved in a database to identify the models of products that had presented more defects and at the same time had the highest demands by customers, and therefore, the highest production levels. In this way, opportunities for improvement were identified and prioritized.

4.1.2. Phase 2. Do

In this phase, the improvements opportunities detected in phase 1 were implemented. Among the implemented improvements were the following:
  • Update of the process sheets for the set of electronic boards.
  • Adjustment of parameters (temperature, speed, and other ones) for different product models.
  • Evaluation and improvement of the design and conditions of the fixtures.

4.1.3. Phase 3. Check

In this phase, the results that were obtained when implementing the improvements of the previous phase were analyzed. For instance, the performance effect of the new fixtures on the number of defects was analyzed. Similarly, the assemblies released from the stations of manual assembly and Touch up were analyzed. Also, data from the last month (June 2018) were collected once the proposed changes were implemented in stage 2.

4.1.4. Phase 4. Act

In this phase, general results that were obtained with the changes made in the process were presented to managers. Based on the analysis performed on phase 3, some changes were standardized in the wave welding process.

5. Results

5.1. Results of Phase 1

Figure 2 shows the layout and flowchart for the Manual Finish area. As can be seen, the production of electronic boards was performed in eight tasks: (1) Manual in, (2) Manual assembly, (3) Wave soldering machine, (4) Touch up, (5) Hand soldering, (6) Inspection, (7) Finish out, and (8) Quality Assurance (Q.A.). Improvement opportunities were detected in the tasks of Manual assembly and Wave soldering machine. The results that were obtained from these improvements are presented in Section 5.2.
The main defects detected in the wave welding process, and that represented the 80.8% of all defects, were solder bridge, damaged component, missing component, wrong component, lifted component, excessive solder, reversed component, insufficient solder, and pin damaged. Figure 3 shows the results in a Pareto chart for the defects that were detected in the Manual Finish area during the period of August to December 2017. Similarly, Figure 4 shows a Pareto chart with the product models that had the highest number of defects. These models were 595407-XXX-00, 595310-001-00, and 595481-00X-00. On the other hand, Table 1 shows the shows the projected demand for one year (February 2018 to February 2019) for the three models mentioned above before carrying out the present project. Note that, for the three models, the projected demand is more than 21,000 units (row of Total). Based on the fact that these models were the ones with the greatest number of defects and also the highest demand, they were the ones that were dealt with in this project. Figure 5 shows the defects that were detected in the model 595407-XXX-00. Similarly, Figure 6 shows the defects detected in the model 595481-00X-00. Finally, defects detected in the model 595310-001-00 are shown in Figure 7.
Regarding the fixtures that were used to perform the welding process, it was detected that several of them were damaged. This condition favored the appearance of defects. Therefore, new fixtures were purchased. These new fixtures presented a new design, since an improvement opportunity was detected in this issue. Table 2 shows the number of fixtures for each model in the company before the project was carried out, how many of them were damaged, how many had to be purchased, and the total cost, in American dollars (USD), to obtain them.

5.2. Results of Phase 3

Based on the improvements that were implemented in phase 2, results indicated that all necessary fixtures were purchased for each model (see Table 2). In the wave welding process, these new fixtures helped to decrease the number of defects in comparison with the old fixtures. Other results indicated that the workstations of Manual Assembly did not have defective parts. Similarly, in the Workstation of Touch up there was an instant improvement, since the touch up process time had a decrease.
Regarding the defects of the analyzed models, results showed that the percentage of defects significantly decreased on the three models, having all of them less than 5% of all defects among all of the models. Figure 8 shows the percentages (in red) of defects for the three models during the month of June 2018 (after the project was concluded). More precisely, the percentage of defects for the model 595310-001-00 decreased 65%. Similarly, the defects for the model 595407-XXX-00 were reduced in 79%, whereas the defects of the model 595481-00X-00 decreased 77%.
At the same time, these results led to an increase in the product quality, since the number of times the electronic boards were retouched was decreased, which in the beginning caused them to wear out, was reduced. Likewise, an increase in production was obtained in the three analyzed models, since the average times in the Touch up stations were reduced. For the model 595310-001-00, the average time in the Touch-up station decreased from 2.1 to 0.73 min; for the model 595407-XXX-00, from 2.54 to 0.53 min; and, for the model 595481-00X-00, from 3.1 to 0.71 min. Table 3 shows the monthly capacity of the Touch up station before the project was carried out.
Table 4 shows the hours earned by model at the Touch up station once the project was completed.
Based on the differences that are presented in Table 3 and Table 4, the results indicated an increase of 19.72% in the capacity of the Touch up station. In economic terms, this percentage represents a saving of $21,027 USD projected to one year, since the cost per operator was $3.87 USD per hour.

5.3. Results of Phase 4

At this stage, results were presented to the managers who approved standardizing some changes in the wave welding process. Some of the standardized changes were the use of fixtures with the new design, the update of visual aids with real photos of the electronic boards, in which notes for the electronic boards with polarity were added, specifying the correct positioning of the board. Similarly, some parameters (temperature, fan speed, wave speed, conveyor speed, conveyor width, flux amount) were changed and standardized for the three models.

6. Analysis of Results

If we make a contrast of the results in this project with the results of other projects that also applied Pareto charts and PDCA, we can state that the results obtained are correct. In all the case studies presented in literature review, Pareto charts were applied to detect the most common defects of a specific product or process. In our project, we detected the most common defects in the welding process of electronic boards by applying Pareto charts. These defects were solder bridge, damaged component, missing component, wrong component, lifted component, excessive solder, reversed component, insufficient solder, and pin damaged. Also, Pareto charts helped to detect the models with more defects. Regarding the application of the PDCA cycle, case studies mentioned above showed that it is a useful method to decrease the number of defects of different process or products. In our case study, results indicated a reduction of defects by 65%, 79%, and 77% in the three models analyzed. These results mean that the application of the PDCA cycle and the Pareto charts was correct. Also, such results imply that the defects we analyzed should not appear more or should show a decrease trend in its appearance.

7. Conclusions and Recommendations

In general terms, it is concluded that the PDCA cycle is a tool that facilitates the detection of improvement opportunities, as well as the development and implementation of the same in lean manufacturing projects. This can be further simplified by the application of support tools, as in this case study were the Pareto charts and the flowchart. Together, the three tools help to globally increase the competitiveness of manufacturing companies, as in the case of the case study shown in this project.
With respect to the objectives proposed in this project, it is concluded that the objective of reducing, at least 20%, the defects generated by the wave welding process in the models with the highest sales volume in the Manual-Finish area was achieved, since the number of defects on the three analyzed models decreased by 65%, 79%, and 77%. On the other hand, with regard to the objective of increasing the capacity in the three double production lines of the electronic boards by at least 20%, it is concluded that also this objective was achieved, since the result was 19.72%, which had a difference of 0.28%, which it is considered to be non-significant. Finally, these results allow the company to be closer to complying with the IPC-A-610E standard, since a high percentage of the electronic boards of the analyzed models managed to meet the criteria established by that standard.
Based on the results in this case study, it is recommended to replicate the PDCA cycle in the other models, present more defects, such as 532053-XXX-00, BOM1500796-XXXS, and 596448-002-00, to name a few.
Throughout the project there were different limitations that at that moment made it difficult to carry out. Among these limitations are the absences of the personnel in charge of carrying out specific activities within the project. These absences were due to different causes, such as disabilities or trips outside the city where the manufacturing company is located. In addition, there were time limitations. This type of limitations arose from the need to buy fixtures with a new design. At the time of placing the order with the design specifications, the supplier already had an important workload to attend to. This caused the delivery time to delay the project and continue using the fixtures without the new design. Both limitations were overcome. In the case of the absence of personnel, another worker was trained in the specific task of the project. This training lasted a week before the person responsible for the activity went on a trip. Regarding to absences due to disability, the doubts that arose were resolved by contacting the responsible person, either by email or by telephone. In the case of the second type of limitation, this was resolved simply by waiting for the supplier to deliver the new accessories.

Author Contributions

Conceptualization, investigation and writing—original draft preparation, A.R.-V. and G.R.; formal analysis, writing—review and editing, K.C.A.-S.; supervision and funding acquisition, T.C.-G.


This research received no external funding.


The authors want to acknowledge to the Tecnológico Nacional de Mexico/Instituto Tecnológico de Tijuana and to the Universidad Autónoma de Baja California for allowing us to use their facilities and resources to develop this paper. Also, the authors want to thank the National Council of Science and technology (CONACYT) and PRODEP for their support to continuing performing research.

Conflicts of Interest

Authors declare no conflict of interest.


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Figure 1. Flight Control platform screen.
Figure 1. Flight Control platform screen.
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Figure 2. Layout and flowchart for the Manual Finish area, where 1, 2, 3, and 4 are the number of the wave solder machines.
Figure 2. Layout and flowchart for the Manual Finish area, where 1, 2, 3, and 4 are the number of the wave solder machines.
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Figure 3. Pareto chart for the defects detected in the Manual Finish area.
Figure 3. Pareto chart for the defects detected in the Manual Finish area.
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Figure 4. Pareto chart for the models with more defects.
Figure 4. Pareto chart for the models with more defects.
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Figure 5. Pareto chart for the defects detected in the model 595407-XXX-00.
Figure 5. Pareto chart for the defects detected in the model 595407-XXX-00.
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Figure 6. Pareto chart for the defects detected in the model 595481-00X-00.
Figure 6. Pareto chart for the defects detected in the model 595481-00X-00.
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Figure 7. Pareto chart for the defects detected in the model 595310-001-00.
Figure 7. Pareto chart for the defects detected in the model 595310-001-00.
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Figure 8. Relative frequency of defects for each model after finishing the project.
Figure 8. Relative frequency of defects for each model after finishing the project.
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Table 1. Projected demand for one year (February 2018 to February 2019) for the three models analyzed.
Table 1. Projected demand for one year (February 2018 to February 2019) for the three models analyzed.
595481-004-00 8149127724945526304625526304625525227354
595481-002-00206 206
Total 21,659
Total 63,523
595310-001-00 18,91612,1308432745672968388619872968388619872966930110,756
Total 110,756
Table 2. Number of fixtures for model, damaged fixtures, optimal number of fixtures, fixtures to be purchased, and total cost.
Table 2. Number of fixtures for model, damaged fixtures, optimal number of fixtures, fixtures to be purchased, and total cost.
ModelFixtures before the ProjectDamaged FixturesOptimal Number of FixturesFixtures to be PurchasedPrice by Fixture (USD)Cost for Total Fixtures (USD)
Total cost (USD)$4220
Table 3. Monthly capacity of the Touch up station before the project was carried out.
Table 3. Monthly capacity of the Touch up station before the project was carried out.
Shifts per day2
Hours per shift9
Hours of rest1
Double production lines3
Net time per day (hours)96
Days worked per week6
Weeks worked per month4
Net time per month (hours)2304
Table 4. Hours won by model at the Touch up station once the project was completed.
Table 4. Hours won by model at the Touch up station once the project was completed.
ModelTimes of the Touch Up (Hours)Hours Earned per Month

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MDPI and ACS Style

Realyvásquez-Vargas, A.; Arredondo-Soto, K.C.; Carrillo-Gutiérrez, T.; Ravelo, G. Applying the Plan-Do-Check-Act (PDCA) Cycle to Reduce the Defects in the Manufacturing Industry. A Case Study. Appl. Sci. 2018, 8, 2181.

AMA Style

Realyvásquez-Vargas A, Arredondo-Soto KC, Carrillo-Gutiérrez T, Ravelo G. Applying the Plan-Do-Check-Act (PDCA) Cycle to Reduce the Defects in the Manufacturing Industry. A Case Study. Applied Sciences. 2018; 8(11):2181.

Chicago/Turabian Style

Realyvásquez-Vargas, Arturo, Karina Cecilia Arredondo-Soto, Teresa Carrillo-Gutiérrez, and Gustavo Ravelo. 2018. "Applying the Plan-Do-Check-Act (PDCA) Cycle to Reduce the Defects in the Manufacturing Industry. A Case Study" Applied Sciences 8, no. 11: 2181.

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