Multi-agent simulation of sawmill yard operations

This paper reports the findings of using multi-agent based simulation model to evaluate the sawmill yard operations within a large privately owned sawmill in Sweden, Bergkvist Insjön AB in the current case. Conventional working routines within sawmill yard threaten the overall efficiency and thereby limit the profit margin of sawmill. Deploying dynamic work routines within the sawmill yard is not readily feasible in real time, so discrete event simulation model has been investigated to be able to report optimal work order depending on the situations. Preliminary investigations indicate that the results achieved by simulation model are promising. It is expected that the results achieved in the current case will support Bergkvist-Insjön AB in making optimal decisions by deploying efficient work order in sawmill yard.

Simulation model using meta heuristic algorithms for achieving optimal arrangement of storage bins in a sawmill yard

Bin planning (arrangements) is a key factor in the timber industry. Improper planning of the storage bins may lead to inefficient transportation of resources, which threaten the overall efficiency and thereby limit the profit margins of sawmills. To address this challenge, a simulation model has been developed. However, as numerous alternatives are available for arranging bins, simulating all possibilities will take an enormous amount of time and it is computationally infeasible. A discrete-event simulation model incorporating meta-heuristic algorithms has therefore been investigated in this study. Preliminary investigations indicate that the results achieved by GA based simulation model are promising and better than the other meta-heuristic algorithm. Further, a sensitivity analysis has been done on the GA based optimal arrangement which contributes to gaining insights and knowledge about the real system that ultimately leads to improved and enhanced efficiency in sawmill yards. It is expected that the results achieved in the work will support timber industries in making optimal decisions with respect to arrangement of storage bins in a sawmill yard.

Simulation of Sawmill Yard Operations Using Software Agents

Bergkvist insjön AB is a sawmill yard which is capable of producing 350,000 cubic meter of timber every year this requires lot of internal resources. Sawmill operations can be classified as unloading, sorting, storage and production of timber. In the company we have trucks arriving at random they have to be unloaded and sent back at the earliest to avoid queuing up of trucks creating a problem for truck owners. The sawmill yard has to operate with two log stackers that does several tasks including transporting the logs from trucks to measurement station where the logs will be sorted into classes and dropped into pockets from pockets to the sorted timber yard where they are stored and finally from there to sawmill for final processing. The main issue that needs to be answered here is the lining up trucks that are waiting to be unload, creating a problem for both sawmill as well as the truck owners and given huge production volume, it is certain that handling of resources is top priority. A key challenge in handling of resources would be unloading of trucks and finding a way to optimize internal resources.To address this problem i have experimented on different ways of using internal resources, i have designed different cases, in case 1 we have both the log stackers working on sawmill and measurement station. The main objective of having this case is to make sawmill and measurement station to work all the time. Then in case 2, i have divided the work between both the log stackers, one log stacker will be working on sawmill and pocket_control and second log stacker will be working on measurement station and truck. Then in case 3 we have only one log stacker working on all the agents, this case was designed to reduce cost of production, as the experiment cannot be done in real-time due to operational cost, for this purpose simulation is used, preliminary investigation into simulation results suggested that case 2 is the best option has it reduced waiting time of trucks considerably when compared with other cases and it showed 50% increase in optimizing internal resources.