I recently came across a post explaining why it is urgent to start going Industry 4.0 with collecting big data. The rationale is built on the example of social media companies who base their business model on big data and paved the way to industry at large. The pitch Just as the social media companies … Continue reading Industry 4.0: Beware of the vendor wonderland
The digital twin is the virtual and digital copy of a factory allowing monitoring, post-mortem analyses, simulations, stress tests, machine learning and much more. As a Lean practitioner having started my Lean experience in the 1980s, I faced the difficulty to get engineers, techs and sometimes foremen to the shopfloor to assess and understand the … Continue reading Lean and the digital factory: is the digital twin the new gemba?
Maximizing the exploitation of critical Capacity Constraint Resources (CCRs), so called bottlenecks, is crucial for maximizing revenue. Changeovers usually have a significant impact on productive capacity, reducing it with every new change made on those resources that already have too few of it. Yet changeovers are a necessary evil, and the trend is going for … Continue reading What data for changeover monitoring and improvement?
In many organizations people capture a lot of data and... just ignore them, wasting their potential value. The latest case, at the moment I write this post, is with an aircraft MRO company. This post echoes a previous one: Trouble with manual data capture Every aircraft undergoing MRO requires a lot of mandatory paperwork for … Continue reading So many wasted data
This weird title “Play big on small data” suggests the utilization of big data principles on small data sets. “Small” is to be considered relatively to huge amount of data big data can manage, which is not necessarily only a handful. I came across big data with former colleagues who were IT experts and got … Continue reading Play big on small data
Asking people to fill out forms in order to monitor performance, track a phenomenon or try to gather data for problem solving, too often leads to trouble when data is ultimately collected and analysed. The case is about manual data capture into paper forms and logbooks on production lines. A precious source of information for … Continue reading Trouble with manual data capture
In this post, I assume in near future correlation will be more important than causation* for decision-making, decisions will have to be made according to “incomplete, good enough” information rather than solid analyses, thus big data superseding Six Sigma. *See my post “my takeaways from Big data” on this subject In a world with increasing … Continue reading Why Big data may supersede Six Sigma
I got my first explanations about Big Data from experts who were my colleagues for a time. These passionate IT guys, surely very knowledgeable about their trade, were not always good about passing somewhat complex concepts in a simple manner to non-specialists. Yet they did well enough to raise my interest to know a bit … Continue reading My Takeaways from Big data, the book
In near future, technology and especially connected objects - smart things stuffed with sensors and so-called wearable devices - will supercharge Lean improvements. One example of such already used device is given in a Mark Graban podcast about Hand Hygiene & Patient Safety. In this podcast (Episode #205), Mark’s guest Joe Schnur, VP Business Development … Continue reading Lean in digital age: sensors and data
5S are meant to be the foundations of operational excellence as no efficient work is imaginable in a messy, dirty and unsuitable-for-quality environment. This is long proven in the “physical world” and until recently transposable into the virtual world of digital information. In short, 5S is a framework for sorting, organizing, tidying, set housekeeping and … Continue reading Can 5S survive big data?