Phelps Kern, Jill (1989, ASQC) Digital Equipment Corp., Marlboro, MA
Companies around the world are waking up to the truth that Quality is a major competitive weapon. In the growing drive to get on the road to continuous improvement (of processes, of products, of services), we are all seeking ways to get the most out of our resources.
In the words of the Quality gurus, we need to focus on prevention rather than detection of problems. That is, it's more efficient to monitor the manufacturing process, rather than inspecting the end product. When a product defect is discovered, it's too late! If we can learn to watch the process and recognize when it is heading in the wrong direction, we can take action and reverse the trend before any bad product is created.
Our tools in monitoring process quality, as well as in improving it once it's in control and stable, are based on analysis of data from that manufacturing process. How we collect, analyze, and respond to such data will make or break our efforts to improve quality, productivity, profitability and competitive position.
Data analysis for quality involves interaction among computers, people, and process machinery. Helping these resources make the most effective use of process data in order to control and improve product quality is the focus of this paper.
I will base the discussion on three stages of development of a quality information system:
Human resources (HR)