A new report by the Automotive Industry Action Group (AIAG) has flagged analytics to identify root causes as one of the critical recommendations in their Quality2020 Survey. The new report is available free from the AIAG website. It looks at data from across the automotive supply chain.
In many assembly and fabrication businesses, one of the biggest challenges I’ve encountered is folks simply Not Knowing Where Stuff Is (NKWSI). They lack timely actionable intelligence about their business operations. This is especially problematic when the product is complex, takes multiple shifts to complete, and involves a lot of people.
French, Spanish, and English now supported [...]
Introduction Version 8.0 of GainSeeker was the first step in [...]
"We were able to reduce the variation in the amount of product put into bottles across a 16-head machine. By bringing all the heads in alignment, we reduced average overpack by two grams. Two grams of our product means absolutely nothing to the consumer. But because of the volumes we run through here, we saved an enormous amount of money, and it all fell directly to the bottom line."
Manufacturers now have more power over the inspection process [...]
Announcing the release of my new eBook "Tripping Over Data - How too much data and not enough actionable intelligence can torpedo your business."
A recent report by Gartner notes that although quality receives strong endorsement and support from executive sponsors: “Only 22% of the respondents in a 2015 Gartner study on quality in the supply chain claim quality as an integrated function of their supply chains, and even fewer report is as a discipline. It's no wonder that over half of the high-profile quality failures of the past decade, ranging from flawed product launches, customer and patient safety incidents, and product recalls, are rooted in the extended value chain.” So how do you go about integrating quality across your supply chain?
GainSeeker Version 8.4 Turns Disparate Data Into Real-time Manufacturing [...]
If you’re struggling to make sense of manufacturing big data, you’re not alone. According to research published last year by The Economist, only 42% of manufacturers have what they consider to be a well-defined data-management strategy. Even more striking, 86% report problems in managing the data they are now generating. According to David Line, Managing Editor, Economist Intelligence Unit, “Manufacturing has been at the forefront of data collection and its importance to quality and cost control is well recognised. But collecting too much data, or failing to analyse what you collect, can be counterproductive.”
