The Repair Bay, Part 2: Why enhanced defect data management should be seen as a positive on the plant floor
With this installment, Patrick Chabot emphasizes that it takes more than tools and processes to turn the repair bay into an effective defect data management station to drive continuous improvement. Buy-in, from the corner office to the plant floor, is crucial.
John Perkins discusses how an ICP-based accelerometer that’s connected to a test monitoring system can keep noise, vibration and harshness (NVH) testing on the factory floor and avoid the cost and complexity of having to use an anechoic chamber.
Ron Pawulski cites a Sciemetric use case to explore how digital process signature analysis can save medical device makers from the cumbersome and costly process of end-of-line destructive testing for quality assurance.
In process testing and digital waveform analysis isn’t only for discrete manufacturing where each part is serialized. Ron Pawulski explores how it can also be used to improve yield and quality control in pharmaceutical and medical device batch manufacturing.
John Perkins recaps a use case for noise, vibration and harshness (NVH) testing. A multi-channel sigPOD platform with a strategically located accelerometer helped a wheelchair manufacturer catch problems with motors and gearboxes during production to avoid warranty claims.
John Perkins cites a use case for noise, vibration and harshness (NVH) testing. Digital process signature analysis using an accelerometer is put to the test against the traditional microphone approach to catch nicked gears in automotive transmissions on the line during production.
Remember that Jurassic Park character, Nedry, who built an IT system no one else could manage? Joe Ventimiglio discusses how machine builders can avoid this mess by not trying to scratch-build a data-driven quality assurance system for a customer.
Machine builders are always struggling to stay on budget, on schedule and on spec with their manufacturer customers. Joe Ventimiglio discusses how incorporating the data-driven quality management of Industry 4.0 into their builds can save them a lot of grief.
We give a primer on how comprehensive data collection from across the plant floor, coupled with digital process signature analysis, can achieve the sometimes contradictory goals of reduced production costs and improved quality.
Does it make more sense to improve the overall yield of a line, or work to reduce scrap and rework rates to boost first-time yield? We crunch some numbers and illustrate the difference that digital process signature analysis can make.