The following case study – the first ever for Inmatic, it illustrates how we learn about, and then intelligently solve
your operations challenges.
The story begins with Hans Kull, an apprentice in a Swiss electro-mechanics firm who discovered a love of solving problems through mathematics.
After finishing his Bachelor of Science in electronics and his Masters in maths, Hans worked for a couple of years in industry on a simulation model, before becoming the department leader for a major Swiss manufacturer of locks and lock cylinders in 1981. His department was in charge of calculating the mechanical codes for the keys and cylinders in master key systems. Back then, this was all done manually and for large and complex systems it could take up to three weeks to work out the correct codes to satisfy the customer’s specifications.
More often than not, in those complex cases they had to go back to the customer too, to simplify the specification in order to make it possible to resolve (given the limited possibilities of a mechanical lock system).
When Hans started the job, a project to computerise the whole calculation and administration was already under way. However, there were some uncertainties on the computing times required and when he started studying this problem, he soon realised that this problem belonged to a class of very hard to solve problems, where computing time grows exponentially with the size of the problem occurring.
In order to overcome this difficult challenge, Hans started listening more carefully to what his staff had really asked him to do: To come up with a solution which would not just automatically generate a solution (which they then would struggle to understand and maintain), but instead to come up with a system that would support that calculation process.
Hans wrote a solution which was able to handle the smaller instances automatically. These solutions where then presented to the specialist so he could modify them before giving them into production.
To solve the big problem instances, they came up with a system that supported the specialists to an extent that turned our biggest sceptic into our biggest fan. As he stated himself, with our software he was now able to solve those very complex problems that would have taken him three weeks before, in only one day.
This had a dramatic effect on the company. Only now, it became clear how much of a bottleneck the department was for the production process. In order to cater for the uncertainties of this, production planning did set waiting times throughout the production process and still there were instances where deliveries could not be made on time.
Now, orders were calculated even before an order confirmation was sent. If a complex instance had to be simplified, this was done before accepting the order and thus before production planning was started. Therefore the waiting times throughout production could be reduced and as a result average overall production time for an order was halved within a few months of introducing the new system. Within one year, turnover almost doubled.
What was learned from this, and what has become a key part of the Inmatic's philosophy, is the importance of empowering people to do their job better.
These days in many companies, people are confronted with complex situations which they have to resolve with crude tools, little computer support and no real understanding of the overall situation. In many aspects, problems have become very complex and optimisation algorithms, although important for getting a good solution, are only a minor part of the solution and the overall programming effort.
Inmatic are experts at solving these problems every day for an endless number of variables, production methods, machines and processes.
The following is a case study showing how Inmatic works with medium and large joineries.
Geoff runs a joinery business in Paramatta, using WoodCam and our optimiser LayOpt. In order to increase productivity he added an automatic feeder to his router and on this he has a label printer
running, to affix the labels to the pieces of the next sheet even before the sheet is cut. This enables him to maximise throughput on the router.
We then pointed out to him that we have a solution where we would schedule jobs together if they have same materials, so he could reduce waste. Geoff realised that this would increase productivity
even more, because optimising multiple jobs together means fewer changes of material in the feeder and thus reduced waiting times for the router.
When skimming through his recent jobs we also found quite a few instances where he could have saved on expensive material if he had scheduled and thus optimised two jobs together. We are currently in the process of thoroughly analysing the savings potential of such a solution (and therefore the fast return on the investment of introducing our software). One problem we are addressing is the sorting out of the cut pieces into the different jobs.
Through this process Geoff is receiving a customised solution and a dramatic increase in efficiency and job profit for his business. Effectively, he is benefiting from being a pilot client in our Joinery products.