Effect of Six Sigma Methodology on Operation Processes
|✅ Paper Type: Free Essay||✅ Subject: Engineering|
|✅ Wordcount: 4061 words||✅ Published: 8th Feb 2020|
This paper focuses on Six Sigma methodology and how it is used to reduce defects and improve operation processes. Six Sigma aims to reduce the amount of variation in processes. Reducing variation results in a lower number of defects produced. Six Sigma is a useful tool that organizations can use to help improve many different areas they might be struggling with. This paper analyzes the Six Sigma DMAIC method and how it is used in specific case studies where the goal is to reduce the number of defects in their processes. The evidence in this research promotes the use of Six Sigma within companies, given that they have the necessary tools to correctly implement the methods.
Six Sigma DMAIC and Waste Reduction
Imagine being the head of a large organization, but your organization is losing profit due to overproduction of waste. What steps would you take to make production processes more efficient? Many organizations today are turning to Six Sigma methods in order to increase operation efficiency. I was first introduced to Six Sigma methodology in my Operations Management class this year at Olivet Nazarene University. I was instantly curious after watching a video on how the use of Six Sigma methods helped Caterpillar reduce the waste that they produced during the manufacturing of machinery. The concept of Six Sigma reducing defects down to 3.4 defects per million opportunities seemed unreachable in my mind. After reading case studies of the results of Six Sigma being carried out, I now understand that 3.4 defects per million opportunities is an attainable goal. As an industrial engineering major, I could potentially go into the field of lean manufacturing. This research on Six Sigma gives me insight to a whole other aspect of this field within engineering that I had no previous knowledge of before.
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After doing a great deal of research, I realized that Six Sigma is very well known and used among companies worldwide. When implemented correctly, it can significantly increase operation efficiency and ultimately cut down on waste and defects produced. This methodology is still growing in popularity today and continually advancing its methods. What is very interesting about Six Sigma is that it continues to progress, but progression does not discard older use of the methods. It is a continually growing methodology where methods used ten or more years ago are still applicable to organizations today.
Review of Research
Six Sigma Methodology
In our world today, people are continuously looking for improvement in all areas of society. In order to achieve improvement in operational processes, organizations might look to implement a methodology called Six Sigma. As stated by Holloway and Nwaoha (2012) in the Dictionary of Industrial Terms, Six Sigma is “a program that originated at Motorola where the objective is customer satisfaction through continuous improvement in quality. Six Sigma means products and processes will experience only 3.4 defects per million opportunities or 99.99966% good”. While 3.4 defects per million opportunities (six sigma capability) is the goal to be obtained, Geng (2015) explains that only about 5% of organizations truly achieve six sigma capability, while the rest of the organizations come relatively close to achieving that desired capability. True perfection will likely never be achieved in any type of process because there will always be some type of random variation that hinders a process and cannot be predicted nor avoided. Geng (2015) simply states the goal of any Six Sigma work as “preventing causes of defects” (ch.37.3). Preventing defects is key to successfully using Six Sigma because, as seen in the case studies examined later, reducing defects increases process capability, reduces cost, increases company and customer satisfaction and overall improves operation processes. Kumar (2017) explains the critical key concepts that Six Sigma focuses on are: Critical to Quality, Process Capability, Defect, Variation, Stable Operations, and Design for Six Sigma (p.2). Focusing on these concepts allows Six Sigma to execute to its maximum capability. Six Sigma is utilized to try and limit variations that might lead to waste, defects, or unproductive processes. By focusing on reducing defects and waste, organizations are able to produce a higher level product or service and reduce costs. In short, the methods Six Sigma aim to reduce the variation in processes, in order to allow them to function at a higher quality by lowering the number of defects in a given number of opportunities.
Six Sigma History
As mentioned in the definition above, given by Holloway and Nwaoha (2012), Six Sigma was originally founded by the Motorola company in the early 1980s. Geng (2015) describes that the development of Six Sigma began when an engineer working for Motorola noticed a difference in products that were produced correctly and products that were initially defective. He observed that the products that were defective during production and had to undergo reworking were high vulnerable to failure during customer use. In comparison to defective parts, products that produced well the first time hardly ever failed during customer use. He came to the realization that even with reworkings, originally defective products were not good enough. Fixing the problems that were causing defects in the manufacturing process was the conclusion that the Motorola Company decided would decrease the amount of defects produced (ch.37.4). This caused Motorola to focus on creating a process that would prevent defects from occurring, if at all possible. Motorola used sigma values to measure the conformance of the defects of products that were being produced. These sigma values represent standard deviations from the process mean and accounted for the variation in the process (ch.37). Porteous (2008) defines standard deviation, in the Dictionary of Environmental Science and Technology, as “the most common measure of statistical dispersion, measuring how widely spread the values in a data set are”. As motioned earlier, the sigma values that represent the standard deviation which account for the variation with in the process. Sahay (2015) also mentions that falling within plus or minus six standard deviations refers to the “maximum acceptable range of noncompliance” (p.18). By setting boundaries and limitations for the amount of variation that can occur, organizations are able to control variation that might occur in their processes. Despite perfection of controllable variation, there is always the chance of random variation that might occur. That is why Six Sigma accounts for 3.4 defects per million opportunities, due to the chance of random variation. Geng (2015) concludes that developing a six sigma threshold, which creates a 99.99966% conformance level, translates to the 3.4 defects per million opportunities that defines Six Sigma today (para. 11).
Six Sigma DAMIC process of analysis
There are many approaches used in Six Sigma to analyze problems and then trying to formulate solutions. The most popular approach in Six Sigma is the DMAIC approach. As explained by Bisk (2018), DMAIC stands for: define, measure, analyze, improve and control. This approach utilizes statistical analysis to search for ways to improve problems within a process (para.2). The Six Sigma DMAIC Roadmap (2018) gives an in detail description of each phase used in this approach. In the ‘define’ phase, project goals and deliverables are determined using tools such as process flowcharts. The ‘measure’ phase analyzes the current process to see where their current performance lies. This phase utilizes data collection, benchmarking, and sigma calculation to gauge their current level of performance. The ‘analyze’ phase is where practitioners determine what is causing the problem. Statistical measures used to help determine the cause of the problem include histograms, pareto charts, scatter plots, time series/run charts, regression analysis, cause and effect diagrams, etc. The ‘improve’ phase is where the Six Sigma team brainstorms and creates a design of experiment that can improve the process. The ‘control’ phase aims to keep in control of the performance of this process in the future using sigma calculations, control charts, and a control plan. Outlined by the Six Sigma DMAIC roadmap (2018), the DMAIC approach is structed with great detail to help give organizations the best chance of success in reaching the goals they set to achieve (para.3)
Six Sigma Defines Waste
Carreira and Trudell (2006) explains that one of the main goals of Six Sigma is to continue to find ways in which a company can reduce the waste that it produces. There are two types of flows that occur in a business; A business will either provide a product and/or a service. A product is an item being produced or transmitted, and a service is something that someone does for a customer. When evaluating such a system, information and data about that process is being analyzed and observed. Each observation made about the process can fall under one of these two categories: generates revenue or adds cost. If an activity does not generate revenue and in turn adds cost and is considered to be waste (ch.3). Carreira and Trudell (2006) categorize waste into seven different types: overproduction, excess inventory, transport, process, rejects/rework, waiting, and unnecessary motion (p.22). These seven areas of waste are what organizations want to reduce in order to avoid extra costs, liabilities, customer dissatisfaction, etc. Sahay (2015) mentions that the flow of the operation is improves and the time it takes to produce products is also decreased when defects and waste are eliminated (p.19). As one can see, the removal of waste in processes not only affects the amount of correctly produced products, it affects several other areas with in a business in a positive way. This is why many organizations are looking for ways to reduce the waste produced in their processes, and Six Sigma paves the way to make that happen.
Six Sigma Case Studies
There are a multitude of case studies that show the difference Six Sigma methods can make in an organization, as well as troubles organizations have with implementing these methods. Throughout all the studies researched, there weren’t any negatives or drawbacks about implementing Six Sigma. In each case study to be discussed, Six Sigma aids the organization in reducing their waste and improving operation processes. Some studies had difficulties initially carrying out these methods, but after a few adjustments they were able to progress forward to see positive results being achieved.
Grinding processes. One case study in which Six Sigma methods where carried out was in an automobile part manufacturing company in India. This method is used to help reduce defects in the grinding process. This company manufactures common rail direct injection system pumps for vehicles which can be used in all types of vehicles from buses to trucks in countries all over. Gijo, Scaria, and Antony (2011) explain the what the fuel injector is with a labeled picture for their readers to visually see what is going to be discussing, and then describe that these fuel injectors allow for delivery of fuel in vehicles (p.1222). Gijo, Scaria, and Antony (2011) report that the amount of rejected pieces that resulted from this fine grinding process was very high. In order to reduce these defects, this company decided to enforce Six Sigma methods. The team that was chosen this project decided to use the DMAIC approach to address this issue (p.1223). How the company utilizes the DMAIC method is broken down and analyzed phase by phase.
Define. The team defined their goal as “the reduction in rejection of distance pieces by 50% from the existing level, which should result in large cost savings for the company in terms of reduction in rework and scrap cost” (p.1222). In this phase of the method, the team also prepared flow charts and a clear understanding of what needs to occurring in the following steps of the approach (p.1223).
Measure. The team then entered into the ‘measure’ phase of the approach where they began to understand the process’s baseline performance. They realized that the rejected pieces were due to different types of defects on the parts, described in the study as uneven surfaces that can cause leakages, that occurred after machining. They were able to collect data by measuring pieces with visual limit sample, which was presented as a pareto diagram (p.1224). The team created a cause and effect diagram to try and determine the potential causes of defects in these parts during a brainstorming session.
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Analysis. In the analysis of the variation, an ANOVA test was run, and significant values (p-values) were determined and used to rule out potential causes of variation between parts. A cause validation plan was created that stated the potential causes and the statistical or experimental tests that would be conducted in order to determine if a specific cause was a valid cause of variation. After validating all possible causes, the conclusion that was made from the tests was that the main causes of variation came from repair batch mix ups, product family to family variation, presence of sand blasting dust, material removal rate, not optimum process parameters, improper settings, and loading and unloading systems (p.1224-1227).
Improve. The team then moves into the ‘improve phase’ where they try to find solutions to these problems they concluded in the ‘analyze’ phase. Experimentation, using factors with different parameters, were conducted to maximize system performance, in hopes that it would lead to reduction in variation. The six factors that the team observed were the load applied, initial load settings, coolant flow rate, upper wheel RPM, lower wheel RPM, and cage RPM (p.1228). Optimum levels for these factors were determined through statistical tests and were implemented while results were observed. By changing the levels of these factors, the amount of variation that was created by the causes discovered in the analyze phase were significantly reduced (p.1229).
Control. The last phase for the team to consider is ‘control’. Sustainability of these parameters is difficult to obtain because it requires standardization. To insure sustainability of their newly created standards, the company carried out audits every three months to monitor the processes (p.1231). To conclude this case study, the company was able to reduce the rejection percentage from 16.6% to 1.19%, using Six Sigma methods and the DMAIC approach (p.1229-1231).
Laboratory billing defects.
In this case study, Levtzow (2013) shows how Six Sigma methods were applied to try and reduce billing defects in hopes that healthcare costs would decrease. Within a six month period in 2009-2010, the Institute of Medicine recorded $1.9 million being paid for lab tests that were not billed. This alarming number of unbilled tests is a result of defects that occurs in the billing process. The intent of this case study is to reduce these defects using the Six Sigma DMAIC approach (p.358).
Define. In order to narrow the goal of the project at hand, the team made up of members from the Institute of Medicine decided to focus their attention on the 27% of unbilled tests which applied to outreach clinic patients. Using a local coverage determination report, they were able to come up with an approximation of the amount of money that was lost due to unbilled tests (p.359).
Measure. The cost of unbilled tests from outreach patients was plotted along with a process control chart to establish a baseline for the current process. They were able to determine that specifically 20% of those unbilled tests were run by two physicians, as well as a few specific tests that were the most frequently unbilled. These most common unbilled tests included Vitamin B12, renal function tests and lipid panels. The current process being run resulted in a sigma of 3.2 which translated to 45,000 defects per million opportunities (p.361).
Analyze. In order to find out what part of the process was creating these missteps, a cause and effect diagram was created. Pareto charts were created that graphed billing defects in dollars against departments, physicians, and tests ordered to determine which areas were producing the most unbilled tests (p.362). The problems that were identified were classified under the four categories of education, coding resources, requisition, and coding processes. As showing in the cause and effect tree, root causes of these problems are identified as well as specific causes that might need immediate attention (p.364). After classifying all potential causes, a chi-square analysis test was run to validate if these are actual causes that need to be addressed (p.363).
Improve. After identifying these root problems, possible solutions were developed. The three areas for improvement that they focused on were revising requisitions for appropriate tests, better education of physicians and managers for ordered tests, and providing feedback to physicians and managers on their performance. After carrying out these changes, unbilled tests defects decreased from 2.5% to 2.6%, which resulted in and increase of $6,000 per month in Medicare bills, meaning significant increase in revenue (p.365).
Control. In order to monitor their progress and continual improvement, they began documenting process changes, supporting process changes, and allowed for recommendations for future plans. A new system was introduced so that billing laboratory tests was done on time when the test was run (p.369). Using the DMAIC method, the Institute of Medicine was able to reach their goal by significantly reduce laboratory billing defects. This led to the increase their overall revenue and decrease healthcare costs.
Six sigma Imperfections
Six Sigma allows for organizations to make great strides in areas they are struggling with, as seen in the case studies discussed. Six Sigma appears to be a flawless methodology but there can be many limitations and obstacles in carrying out these methods. Geng (2015) describes that one of the biggest obstacles for Six Sigma success is lack of sufficient leadership. In order for these methods to be fruitful, organizations need involved executives who lead well. Guidance from a Six Sigma expert is required because they have been trained in these methods and are able to help the organization stay on the right path. Another reason that Geng (2015) mentions as being an obstacle is the lack of sufficient resources such as funding, staffing, information systems, etc. (ch. 37.8). Stevenson (2012) also says a reason for Six Sigma failure is “lack of sustained executive sponsorship and commitment” as well as “lack of buy-in, cooperation and ownership from frontline managers and employees for implementing and sustaining results on Six Sigma project solutions” (p.395). Fursule, Bansod, and Fursule (2012) also deduce that the main obstacle in applying Six Sigma is the organizations management and employees. Fursule, Bansod, and Fursule (2012) emphasize how important support and execution of Six Sigma lies on the top management of the organization. This dependency causes limitations in carrying out Six Sigma for the reason that top management is concerned with increasing profits, while the methodology is concerned with achieving high quality (p.6). The causes of Six Sigma limitations and failures have to do more with the organization rather than the Six Sigma methods. Lack of commitment, leaderships and funds within the organization cannot support Six Sigma and that is why there are limitations to this methodology.
From the research that I found, organizations that implement Six Sigma methodologies are very likely to see substantial improvement in their operation processes. From the cases that I discussed earlier, both organizations were able to reduce their defects in their products substantially. There are many other case studies similar to the ones already discussed that have the same effects. Even though troubles that may occur while initially attempting to carry out these methods, if Six Sigma is able to be implemented correctly, it always produces positive results. Although it is very difficult to achieve Six Sigma perfection, organizations are able to come very close to that and take their operations to a higher level.
Based on the articles, books, and case studies that I have read, I would recommend every organization to implement Six Sigma methods who have resources and capability to enforce it. Even though Six Sigma is worked with by engineers does not make it exclusive to fields with in engineering and manufacturing. Six Sigma methods can be applied to any problem an organization has because it is generalized through its approaches to fit any scenario. This methodology is not a perfect science and the way that it is used will differ from company to company, but using these methods has allowed organizations to greatly advance beyond their expectations and are able to reach their goals of reducing waste, defects and costs. Overall, I have observed that Six Sigma is a methodology being implemented in organizations worldwide, in order to reduce waste and improve operation process efficiency.
- Bisk. (2018). How does six sigma work? Retrieved from https://www.villanovau.com/resources/six-sigma/what-is-six-sigma/#.W7VGZi-ZNp8
- Carreira, B., & Trudell, B. (2006). Lean Six Sigma that works: A powerful action plan for dramatically improving quality, increasing speed, and reducing waste. Broadway, NY: AMACOM Publishing House.
- Geng, H. (2015). Manufacturing engineering handbook. New York: McGraw-Hill
- Gijo, E. V., Scaria, J., & Antony, J. (2011). Application of six sigma methodology to reduce defects of a grinding process. Quality and Reliability Engineering International,27(8), 1221-1234. doi:10.1002/qre.1212
- Holloway, M. D., & Nwaoha, C (2012). Dictionary of Industrial Terms. S.1.:John Wiley & Sons.
- Levtzow, C. B., & Willis, M. S. (2013). Reducing laboratory billing defects using Six Sigma principles. Laboratory Medicine, 44(4), 358-371. doi:10.1309/lmcvv5ox4f5xafjy
- Porteous, A. (2008). Dictionary of environmental science and technology. Hoboken, NJ: Wiley.
- Sahay, A. (2016). Managing and improving quality: Integrating quality, statistical methods and process control. NY: Business Expert Press
- Six Sigma DMAIC Roadmap. (2018). Retrieved from https://www.isixsigma.com/new-to-six-sigma/dmaic/six-sigma-dmaic-roadmap/
- Stevenson, W. J. (2012). Operations management: Theory and practice. New York, NY: McGraw-Hill/Irwin.
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