Oven Usage Optimization : A study on scheduling at the wear edge production at Olofsfors AB

Abstract: Olofsfors is a steel product manufacturer in Nordmaling, Sweden, producing steel edges for snowplows, tracks for forest machines, and wear edges for buckets on heavy equipment. Most of their products are heated to 900◦ C and then cooled down in water, so-called quenching, during the hardening process. A group of ovens and quench machines together form an oven system and this is used for the hardening. Since it takes a long time for the ovens to reach operating temperature, they are always kept on, which is why it is important to utilize them as effectively as possible. This project investigates the potential utilization increase of one of the three oven systems in the wear edge production unit. This oven system is part of a production line that consists of a saw and a mill, and can process products up to two meters in length, and is hereon called the two-meter line. The two-meter line has a natural inflow through the saw, but raw material produced in other parts of the factory can also be fetched from another inlet. The use of the other inlet is limited by the operator of the two-meter line who has to fetch the material with a forklift. This could be automated so that the operator would not have to handle this inlet. The purpose is to investigate the potential increases in utilization of the oven system for different degrees of automation in order to make the most of the machines and the operator at the two-meter line. In the end, a recommendation is given with a set of ideal properties of the investment that could improve productivity the most. The main method applied in order to explore the potential use of the oven system is a re-entrant flow shop scheduling model. As preceding steps, the production line is first mapped in order to find potential routes for different product families, then the order quantities in the production data are translated into jobs to be scheduled with the help of packing problems and batching rules. The scheduling model of the production line is then solved heuristically with a genetic algorithm based on the sequence of jobs entering the production line followed by a method for creating a deterministic schedule based on this initial sequence of jobs. Lastly, a sensitivity analysis is applied to the processing time for the steps performed by the operator to evaluate the results' robustness. The conclusion is that there is a substantial potential to increase the utilization of the oven system of the two-meter line. The largest potential is when the operator is not actively working at the production line; a maximum of 15.6 h on average. There does also exist a potential to increase utilization while the operator is working at the production line; a maximum of 3.9 h on average. The automation degree needed is high in both cases but due to different reasons. When the operator is not working, the automatic solution needs to work without supervision for longer periods of time, while, in the other case, it needs to be smart enough to adjust to not disturb the operator’s work. For the future, the recommendation is to focus the next step on finding investment options that could exploit the time when the operator is not working. By further specifying the potential investment alternatives, the cost factor can be added to the analysis as well.