Blogs

Vraag een productiemanager hoeveel werkwijzen er in zijn fabriek zijn, en hij zegt: één. Vraag het daarna aan drie operators van drie verschillende ploegen en je krijgt drie verschillende antwoorden. Hoe voorkom je grote verschillen in werkwijze en kwaliteit?

Elke fabriek heeft verstoringen die blijven liggen omdat niemand precies weet van wie ze zijn. De operator wacht op de Technische Dienst (TD), de TD wacht op een werkopdracht. En intussen staat de machine stil. Niemand doet het fout, de grens is gewoon niet duidelijk.

Almost every production manager recognizes this pattern: something goes wrong, you perform a Root Cause Analysis (RCA), adjust the procedure, and add another checkpoint. A few weeks later, someone is standing at your desk with the exact same problem again. The checklist has become longer, but the disruption hasn’t become any shorter. How do you solve this?

Many organizations know they need to do something about knowledge retention. The expert who has been working on the line for thirty years is about to retire. Yet the project keeps getting postponed, because where do you even start? And who has time for such a massive project? What many don’t realize is that it can actually be very simple. With a small first step and a predictable outcome. We’ll show you how.

When you introduce a new system on the shop floor as a production manager or team leader, resistance is common. And that’s something to be happy about. It’s a sign that your people are thinking and engaged. You can use that to your advantage for a successful implementation. How to approach it? We explain.

ELICIT works exceptionally well for specific knowledge challenges. However, this does not apply to every situation or organization. When is ELICIT the right fit for your challenge? These three questions make it clear.

Knowledge management tools all promise the same thing: capturing knowledge, supporting operators, and speeding up training. But how do they actually differ? And which problems do they solve for you? We discuss three well-known solutions, POKA, EZ GO, and ManualMaster, and compare them with ELICIT.

You have fifteen operators on the shop floor. Three of them have been working there for more than twenty years. And yet the line comes to a standstill as soon as that one operator, let’s call him Joe, is not there. How is that possible, with so much experience on the floor? And how do you solve it? You’re probably looking in the wrong place.

They walk your shop floor: those few senior operators who know the machines inside and out. When something goes wrong, they get the call. Great to have people like that, right? Yes, until they leave, get sick, or retire. And then it turns out your production grinds to a complete halt without them. How do you prevent that?

You’ve known for a while now. In eight months, he’s retiring. ‘Bob’, who has been working on line 3 for 38 years. Bob, who can tell at a glance whether the mixer is running right. Who can explain within five minutes why you had quality deviations last week and what you need to do to prevent them. That Bob is about to leave, and he’s taking all his knowledge with him.

When a production line comes to a standstill, we often point straight to the technology: a faulty sensor or a glich in the system. But the reality is completely different: long downtimes, poor performance, and inconsistent quality are mainly caused by lost experience and work methods that aren’t properly passed on. Research by McKinsey confirms this. To achieve real improvement, we need to look at people.

Overall Equipment Effectiveness (OEE) is an excellent method to measure your machine efficiency. But how do you turn measurements into concrete improvements? By combining it with a knowledge base filled with (expert) knowledge. How does that work? Let us explain.