CDN55365 Lean Six Sigma implementation

Student: Allan Sharrock

Course Number: CDN55365

Keywords: Six Sigma, Define, measure, analyze, improve, and control (DMAIC), Large-scale industry, Food-processing industries, Indian industries

Curbing variation in packaging process through Six Sigma way in a large-scale food-processing industry

Darshak A. Desai-Parth Kotadiya-Nikheel Makwana-Sonalinkumar Patel

Source: Journal of Industrial Engineering International Published 27 Aug 2014 Volume 11, pg 119-129

Summary: The article is a case study of a complete Six Sigma pilot project in a large-scale dairy manufacturing plant in India (Desai, Kotadiya, & Makwana, 2015). The company is not mentioned by name but it was referred to as a large-scale milk product company in the country. The specific problem that the team wanted to solve was how to reduce variations of the weight of milk powder in the pouches they are placed in.

The company currently uses automation in the packaging line. This automation process would naturally be more precise and have fewer variations than if each pouch was filled by humans. However, even with this automation the there was too much variation in the packaging. This resulted in lost revenue for the company.

The company started the DMAIC process and followed the steps in an LSS project. They clearly defined their problem statement as, “To reduce the variations in the weight of 1 kg milk powder pouch,” (Desai, Kotadiya, & Makwana, 2015). The company then created a CTQ tree. After the CTQ tree, they did measure the pouch weights with 25 samples and a subgrouping size of 36 (Desai, Kotadiya, & Makwana, 2015). It was determined that they had a sigma level of 3.24.

Once they determined their sigma level they had three root cause analysis sessions. They broke down the root causes analysis methodology into three parts. They were root cause-open, root cause-narrow, and root cause-close. In the root cause open they had a brainstorming session that identified 13 probable causes. In the root cause-narrow, they had a series of multi voting sessions and narrowed down the probable causes to 8 factors. Once they had narrowed down the root causes they then conducted a root cause-close session in which they used the “five-why” technique on each of the 8 probable factors.

Once they had the problems identified they moved on to the improve stages of the DMAIC process. The company had a current defect rate of 25 items out of 37,500 produced (Desai, Kotadiya, & Makwana, 2015). They wanted to improve the percentage by 50% so they needed a defect rate of 12. If the company achieved this goal they could increase their Sigma level to 4.53. To achieve this they developed a system to check the various items in the root cause analysis stage. They also developed a better computer system and maintenance plan.

Once the implemented the improvements the company then transitioned to the control phase in the DMAIC process. The company sought to conduct periodic reviews of the different measures by spot-checking the recommendations and checking the control charts.

Critique: The material present did a good job overall explaining the DMAIC process as learned in the book. This article used a lot of similar terminology and tools as described in the book. The article even touched on a calculation that is being used in my Production Operations Management class. The calculation in question is where we used part of a Balanced Scorecard (Russell & Taylor, 2019). One of the differences is the lack of lean mentioned in the article. The article mostly focuses on the statistical aspect of Six Sigma. Another critique I have is that with the implementation of 8 different control measures the company doesn’t know which control measure had the greatest impact. However, I could see why a company may wish to gain a 50% improvement in the short term to increase profitability. Once that goal is achieved it is important to see how they can best maintain that improvement. Once that is done consistently they could probably better measure how the various factors impact their Sigma level.

References Desai, A. D., Kotadiya, P., & Makwana, N. (2015). Curbing variations in packaging process through Six Sigma way in a large-scale food-processing industry. J Ind Int 11, 119-129. Russell, R. S., & Taylor, W. T. (2019). Operations & Supply Chain Management. Hoboken: John Wiley & Sons, Inc.