Globalization and digitalization have intensified competition in manufacturing. Some companies are using Bayesian hypothesis testing to optimize processes and make informed decisions. For example, a production manager could use it to improve the engine-cylinder-head-machining process.
Reliability analysis helps manufacturers predict and prevent product failures, improving overall quality and performance through systematic assessment and data-driven improvements.
DOE is a method that helps manufacturers improve processes by understanding the relationship between factors and the output. It involves defining the problem, selecting the right design, conducting the experiment, analyzing the results, and implementing changes.
Regression analysis helps quality teams improve their process standards. In simple terms, it helps these teams understand how variations in the manufacturing process affect the quality of the final product.
Every organization can benefit from continuous improvement. In this blog, we’ll highlight 3 simple Lean tools for process improvement, why they’re important and how Minitab Engage can help you successfully leverage these tools across your organization. Let’s get started!
Continuous improvement is essential for business success. These five principles of CI will help you ensure that the improvements you’re striving for are constant, improve all areas of your organization, and deliver value to your customer.
Making statistical mistakes is all too easy. Statistical software helps eliminate mathematical errors—but correctly interpreting the results of an analysis can be even more challenging.
Companies with robust quality programs often struggle to make sure that projects are on track and deliver results—and to aggregate data from thousands of projects so executives can see their overall impact.
