Abstract
The in-plant supply has a great impact on the performance of manufacturing operation, because the manufacturing-related logistics operations influence the efficiency of manufacturing. There are different solutions to perform in-plant supply, in the automotive industry the milkrun and water spider solutions are widely used. Within the frame of this article the authors describe the optimization of milkrun routes in the manufacturing plant of an automotive supplier. The described methodology simplifies the problem for single- and multi-milkrun problems and the solution is demonstrated with an Excel Solver-based methodology. The optimization process and its practicability will be demonstrated through an example.
Highlights
The permanently increased demands of customers are significantly changing the role and operation of the automotive industry
In the logistics systems of automotive suppliers, long lead times are linked to production logistics processes, and all companies are trying to find suitable solutions and reduce the lead time of production logistics
It means the scheduled delivery and replenishment of raw materials and components used in production The advantage of milkrun systems is that the trolleys used to implement them can be flexibly extended and, in addition to the supply of raw materials, they can transport the waste and scrap generated in production, i.e. a raw material cycle can be established [1-3]
Summary
The permanently increased demands of customers are significantly changing the role and operation of the automotive industry. Milkrun is a system for the replenishment of raw materials at specific time, in varying quantities but, as a matter of principle, in similar sizes. It means the scheduled delivery and replenishment of raw materials and components used in production The advantage of milkrun systems is that the trolleys used to implement them can be flexibly extended and, in addition to the supply of raw materials, they can transport the waste and scrap generated in production, i.e. a raw material cycle can be established [1-3]. The authors present an optimization algorithm that is suitable for the design of complex milkrun-based material supply systems in industrial environments. A solution method is presented using a practical example of an automotive supplier, which uses the capabilities of Excel Solver for batch execution to determine the optimal design of a large-scale in-plant supply chain for a milkrun system
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