As an engineer I recommend looking at the quality characteristics required in the physical transformations and instrumenting the flow of work accordingly. I work in many process industries where flow meters, in-line pH meters, temperature and pressure sensors, as well as vibration analysis are all helpful in gaining predictive knowledge of process flows. I never compute COQ or COPQ from this data but apply it to help gain the situation described by Walter A. Shewhart in his 1931 book as the state of "Maximum Control." As an engineer, I see to eliminate the causes of poor quality performance through the design function. This means that there should be no reasons for failure left in the system that will adversely affect its performance. In physical flow systems this is possible, except for variation in the material flows which create "stages" in continuous flow production - each which must have a unique design for its own control limits based on the changes in material conditions. However, this is all controllable. In these states "design quality" obsoletes COPQ statistics! Focusing on activity cost drivers during the design phase is the best way to go rather than to keep using regressive indicators related to cost systems which have their own problems due to the accounting rules under which they are maintained. Anyhow, IMHO, I think that this is the way of the future as we get an increased control over our operational data and their potential for enabling adaptive feedback loops.
I have spearheaded projects on Disamatic Lines for Grey Iron/ Nodular Iron, Automatic Die Casting Machines, and CNC Machines with integrated cellular manufacturing. Robots are used for loading/ unloading applications. This resulted in continuous single piece flow as described by Greg.
The processes were subjected to the fundamentals of using DFMEA/ PFMEA and referenced in the book by Juran ”Quality by Design”. The process controls included online temperature evaluations using infrared gages; metal flow measurements by electronic gages; force, and pressure measurements by transducers, dimensions measurements using laser sensors. These measurements are integrated online SPC using Minitab. PPM and COPQ are the outputs for the KPI metrics/ Lean Six Sigma review.
This particular system has been in place for 20+ years. Continuous Improvement is a part of the QMS strategy of the company approach viz. PFMEA Severity Occurrence Detection (SOD) action plan indicated the variation in measurements of the dimension was observed. Change over from optical sensors to laser sensors was done, 4 years back.
Best Regards, the
QMS Lead Auditor-independent contractor
Partial-Load Professor, Sheridan College
ASQ Education Chair Section 0402
Yes, your implementation is what Grace referred to as perhaps a level 3 application. However, as systems become more digital, then they can apply software robots (AKA - "bots") to collect data that drives cost. These systems are being developed in a number of new applications and Robotic Process Analysis (RPA) is applied in several companies in Finland using software methods like: Blue Prism and UIPath. An new application from Microsoft is UI Path. Capturing cost-driver data at the source is the best way to implement the financial costs from lack of quality as detected in process issues. However, this is typically a very advanced company and lies beyond the application that Girish has cited.