That's what I observed as well. Finding that generic but valuable use-case is quite tough. Selling it is on a totally different level. The impact it can have should be well worth it though
Interesting, that is my experience at Pfizer as well, where I lead projects end-to-end, from problem discovery to solution deployment and I pretty much did everything, from talking to coding
Fewer and fewer people are interested in manufacturing jobs, especially the less glamorous ones. Large manufacturers are having a hard time using analytics and more advanced systems because of qualified labour shortages. I've spoken to manufacturers whose technicians can't even write or follow instructions correctly. Sometimes, sending 10 technicians to inspect an asset would results in 10 different opinions about possible issues / failures. All of these could lead to lower quality product and increased unscheduled downtimes, lower revenues etc etc. But, it is definitely important to still allow people to use their brains and come up with better options
I've started looking into CO2e reduction techniques as well. Would be great to discuss. Working with a client in the food space who is doing this just to learn more
Tracking stuff is hard. I wonder why QR codes won't work in this case, or something similar, or super basic otherwise / stickers or codes at first. Might be more annoying to generate and maintain them initially. CV could work really well to keep track of inspection steps as well, or to recommend what you should do next, and how to do it
Spot on, many of these challenges are common across the board - from my father's plant to Pfizer and others I got the chance to work with. There is however a massive talent gap when it comes to high quality software / ML people in these industries as well. It's tough to get experts to generate quality data and 'recipes' for others to follow when their KPIs are not aligned. Maintenance and reliability don't seem to be sexy enough areas for management to invest in, especially if the value proposition is anecdotal at best. Would be great to chat about your approach for solving some of the above
Many companies store huge amounts of documents, but every team does it in its own way. One template can quickly result in thousands of variations. If robust documentation principles are not used from the very beginning (checklists / reduction in free text, visual indications, etc), it will be a nightmare to make sense of that data afterwards. Also, there is no value in generating large amounts of text data unless you can easily scan it and retrieve the information of interest
Definitely, transfer can only happen when knowledge is organised and understandable by a variety of stakeholders, with different backgrounds (education, languages spoken, years of expertise)