Reducing process variability using control charts

The quest to reduce process variability should be continuous. It is moreover essential for enterprises to improve and control business or manufacturing process outcomes.

Companies that have embraced this culture have been capable of providing service differentials or quality levels and is a sure path to reaching six-sigma levels, resulting in gains in efficiency, reduced costs, fewer nonconformities (less than 4 nonconformities per million) and, ultimately, an edge in the market.

In this article, Daniel Lago shows how to reduce variability in processes by using control charts, a proven, easy to implement and low-cost method. You will learn how to interpret control charts, detect abnormal variability patterns and correlate them with controllable causes.

Lingua: English

Autore

Daniel Lago

Daniel Lago is the founder of SoftLink Technologies LLC, a consulting and systems implementation company based in Atlanta. He is specialized in transformation programs related to product management and quality. Daniel leads the Atlanta chapter of PDMA (Product Design and Management Association). In addition to holding an Electrical Engineering degree, he studied TQM in Japan at the Institute of JUSE (Japanese Union of Scientists and Engineers).