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Six Sigma Methods Improve Manufacturing Efficiency and Confidence

Statistical analysis reduces errors and failures, leading to a far greater number of products manufactured to customer specifications.

More than just another production fad, Six Sigma is a methodology, driven by data, by which manufacturing facilities can work towards fully eliminating defects. The central principle of Six Sigma is that data can be used to drive manufacturing to achieve at least six standard deviations between the mean and the nearest specification limit; in other words, to produce no more than 3.4 defects outside of customer specifications in each one million products. By assessing process performance with Six Sigma statistical representations, manufacturing facilities can greatly increase productivity, efficiency, and cost savings.

This article will describe Six Sigma implementation and success as experienced by Bally Ribbon Mills (BRM), an industry leader in the design, development, and manufacture of highly specialized engineered woven fabrics. The lessons learned by the BRM team can be applied across a wide range of manufacturing applications.

Implementation

Given the highly critical nature of BRM’s products, the company is currently certified to multiple industry quality standards (ISO 9001, AS 9100, and ISO 13485). However, the company’s journey in best quality practices began many years ago with the implementation of MIL-I-45208 and MIL-Q-9858 for its military products. Trends in the automotive and aerospace industries in the 1990s drove BRM to implement additional statistical tools in its quality management efforts. Seeing value in these practices, BRM sent its first employee for Six Sigma (6∑) training. As a direct result, that individual worked on a project that saw a 77% decrease in waste in the production of a single item. It was here that BRM truly recognized the immense value of 6∑ training and began to broaden the scope of the methodology’s influence on their manufacturing processes.

Over the next few years, two more individuals were trained as Six Sigma Black Belts, and the company saw a 30% reduction in waste, overall, during the first two years of the program. After some time maintaining this level of quality in manufacturing, company leadership decided to expand its 6∑ program even further, sending additional personnel to be trained as green belts and Lean 6 to provide additional support to the Black Belt projects. Currently, BRM is training and adding more certified persons each year to the program and driving internal knowledge. Similarly, instead of one computer station with a 6∑ software license for statistical analysis, the company has multiple. All of these changes to program implementation drive improvement in working with customers, management, supervisors, and all other employees on the floor.

With only one or two trained individuals, the entire burden of data collection, entry, and analysis was on those select employees. This not only led to problems of knowledge loss during inevitable employee turnover but also formed a bottleneck in terms of quality management, reducing the scope that these trained professionals could work within. Once a number of people had been trained and the company acquired multiple licenses for software, the QA teams were able to support one another in collecting data and analyzing data, and to let each individual employee succeed in the area of managing quality that they were best suited towards. It has also allowed BRM to distribute trained individuals across functional areas and industry focuses so that the QA program has both a broader impact across the company and a more targeted impact within individual sectors.

Impact

The greatest impact of implementing 6∑ methodology has been the improvements in data collection and analysis: 6∑ trained employees can truly make the data work for a manufacturing process. People who understand what the data means collect better data from the start, and thus help to achieve better results. Well-trained, quality assurance (QA) teams knowledgeable in 6∑ methodology can use the same data than most manufacturing facilities already collect, and still get to a better confidence level, lower material use, less waste, lower lead times, and reduced overproduction compared with other QA methodologies.

BRM began its 6∑ implementation with projects that had shown to be highest priority in terms of risk of failure, highest waste costs, or greatest disruption to the manufacturing area. In these projects, the QA teams can perform statistical analysis on all hypotheses about failure causes and solutions, and by doing so can narrow down to workable potential fixes that reduce variation in final products.

In the past, most quality assurance work came about after a product was developed and had begun to be manufactured. This led to larger tolerances than necessary, and greater waste. Now, using 6∑ statistical tools, the QA teams work alongside the design and manufacturing teams to design new machine setups and more precise production from the very beginning.

As a result, the teams have seen great success in recent years. One project has reduced rejections by 80%, and another reduced the internal rejection rate by 92%. In both of these cases, hypotheses about changing processing time and temperatures have been statistically proven to yield better results for the final product, and so have been implemented.

Benefits for Customers

Implementing 6∑ methodology has helped BRM to communicate more effectively with customers. Customers are now able to discuss product developments via electronic communications, as the experts at BRM work on product development and quality management. The 6∑ methodology had provided both BRM and its customers with better tools to work together while using the same language for goals and the process of achieving them.

Beyond the benefits of communication, 6∑ methodology has enabled some of BRM’s customers to achieve tighter tolerances for materials and design. Additionally, the 6∑ QA efforts have reduced the cost for customers due to greater manufacturing efficiency and greater confidence in tolerances such as thickness, weight, and tensile strength. Customers can have greater confidence in the products they receive from initial production runs, and can thus design their final products to be closer to their ultimate goals.

Conclusion

Overall, implementing 6∑ methodology had had a significant impact on manufacturing, design, and customer relationships for Bally Ribbon Mills. The company is more able to design and manufacture products exactly to customer specifications, and with far greater confidence in finished products than ever before. This saves costs for both the manufacturer and the customers and leads to higher-quality products in use in critical applications such as safety equipment, automotive parts, aerospace components, and more.

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