Ordering and inventory control at ARPS

Abstract: Abstract Title Ordering and inventory control of raw materials at AR Packaging Systems Authors Hedda Trönnberg and Hedvig Orvenholt Supervisors Ph.D. Jan Olhager, Lund University, Faculty of Engineering, Department of Industrial Management and Logistics Max Ivarsson, Supply Chain Specialist, AR Packaging Systems AB Examiner Ph.D. Louise Bildsten, Lund University, Faculty of Engineering, Department of Industrial Management and Logistics Background AR Packaging Systems in Lund (ARPS) is relocating to smaller premises and the substantial decrease of available storage space will require sufficient inventory control. As ARPS wishes to maintain low procurement costs as well as reaching a service level at 99% towards their customers, there is a need to formulate an efficient strategy applicable for this specific case. Purpose The goal with this master thesis is to develop and formulate a strategy for cost optimal ordering and inventory control regarding raw materials from AR Packaging Flexibles to ARPS’ production. Methodology This master thesis has been conducted with an abductive approach, where gathering of quantitative and qualitative data has been iterated. This confirms valid, reliable and objective results. Using triangulation, Fisher’s model for conducting empirical research has been used as a framework for developing an optimal solution from case studies to be used in practice. Result Demand for all raw materials was modeled and showed a great variety in pattern. It was found that all raw materials but three have a large coefficient of variance and relatively low demand. Three different propositions were developed regarding a strategy for how ARPS should tackle these large demand variations considering future space restrictions. Conclusion The authors recommend for ARPS to classify products according to coefficient of variance, where no stock should be kept for customers with a value larger than 1. Further, the solution should be tested and implemented under current basis in order to avoid any unexpected operational challenges.