Improving the On Time elivery performance by the ...

Improving the On Time Delivery performance by the implementation of a Sales Inventory & Operations Planning process

Taking into account the optimization of inventory parameter settings of components with different demand patterns

Master Thesis Final version ? 25 November 2015

S. Donderwinkel, BSc Industrial Engineering and Management University of Twente

Supervisors University of Twente: Dr. P.C. Schuur Dr. Ir. Ahmad Al Hanbali Supervisors Power-Packer Europe M. Rindt H. Langenhof

University of Twente Faculty of Management & Governance Postbus 217 7500 AE Enschede

Power-Packer Europe B.V.

P.O. Box 327 7570 AH Oldenzaal

Master Thesis

Improving the On Time Delivery performance by the implementation of a Sales Inventory & Operations

Planning process

Taking into account the optimization of inventory parameter settings of components with different demand patterns

Author: S. Donderwinkel, BSc

Supervisor Power-Packer Europe: M. Rindt ? Logistic Manager H. Langenhof ? Logistic Team Leader

Supervisors University of Twente: Dr. P.C. Schuur Dr. Ir. Ahmad Al Hanbali

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Management summary

This Master thesis provides an analysis of the On Time Delivery (OTD) performance in the Special Vehicles & Equipment (SV&E) market at Power-Packer Europe and lays a foundation for an improved inventory management system in combination with the set-up of a Sales Inventory & Operations Planning process to improve the OTD performance. The current OTD performance is, with an average of 70% (fictitious number), far below the 95% target, see figure 0-1. The On Time Delivery (OTD) analysis revealed that the major root cause for the poor performance is the material supply, which means not all

OTD Performance SV&E

100%

90%

80%

70%

60% 50%

Confidential

40%

30%

20%

10%

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Oct-14 Nov-14 Dec-14 Jan-15 Feb-15 Mar-15 Apr-15 May-15 Jun-15

necessary components are available to start the production of

a certain product on time.

Figure 0-1 OTD Performance SV&E Due to lower prices abroad, Power-Packer Europe shifted from

local component sourcing to component sourcing abroad. This resulted in longer supplier lead times and thus a

less flexible supply chain. For the serial production in the Automotive and Truck business this does not cause many

problems because customers provide forecasts more than 12 months upfront. However, the SV&E market depends

on single incoming orders which should be delivered to the customer within 5 weeks. Currently the inventory

system is not organized to properly deal with these intermittent demand patterns in the SV&E market, which

results in a poor On Time Delivery (OTD) performance towards customers. Therefore the following main research

question has been formulated:

"How can Power-Packer Europe improve the On Time Delivery (OTD) performance in the Special Vehicle & Equipment market, based on a customer lead time of maximal 5 weeks?"

This research question is answered quantitatively by (1) the introduction of a component classification model based on the component lead time, value and demand pattern and (2) a foundation for a new inventory replenishment policy and forecasting method suited for the complex intermittent demand pattern which is common in the SV&E market. The qualitative part is represented by the implementation of a Sales Inventory & Operations Planning process.

The component classification model at Power-Packer, which is mainly used to determine safety stock, is only based on supplier location and component value but does not take different demand patterns into account. Because of this, the calculation of the safety stock quantities only works for smooth demand patterns. We propose a new component classification model, which distinguishes components also based on lead time and demand pattern. Four main demand patterns can now be classified; Smooth, Erratic, Intermittent and Lumpy, see figure 0-2. Based on this classification the right

inventory parameter settings, like required safety stock quantities Figure 0-2 Demand pattern classification and stock on hand, per component can be determined more accurate to meet the On Time Delivery service level. Besides this, the classification gives a good indication which components are risky to purchase abroad. For example, components showing a lumpy demand should be sourced locally if possible.

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