Aim
The course aims to deepen the students’ knowledge and understanding of methods for management of production and inventory systems, both from a theoretical and applied perspective. An important aspect is to enhance the students’ ability to structure and manage complex tasks, processes and assignments in the form of projects.

Knowledge and understanding
For a passing grade the student must

• be able to use advanced quantitative methods for management and evaluation of production and inventory systems,

• show the ability to independently structure and solve project assignments of investigative nature.

• understand the basic principles of the Toyota Production System which is the basis for lean production.

• understand the challenges and impact of uncertainty and variability on the management of manufacturing systems and to deal with these issues through the use of relevant methods.

• understand the limitations in commonly used production control models, and quantitative modelling of these systems. An important issue that the student must be able to analyse is the strengths and weaknesses with “Pull” oriented CONWIP systems in relation to “Push” oriented MRP systems.

• understand the principles for hierarchical planning of production and personnel, scheduling and shop floor planning within a “Pull” oriented production system. Moreover, to be able to apply quantitative models to improve the control at all these levels.

• critically examine and choose an appropriate model description to effectively manage commonly seen production systems. A special focus is placed on generalised KANBAN systems (CONWIP systems). This is contrasted to the MRP based systems studied in the course MIO030 Production and Inventory Control.

• be able to explain, apply and evaluate different types of quantitative models for efficient control of CONWIP type systems.

• correctly perform statistical analysis of data from stochastic processes that constitute input data to quantitative production and inventory control models. A special focus is placed on analysis of customer demand data and different types of process and activity times. This involves, among other things, fitting of distribution functions and various types of hypothesis testing.

• understand different principles for determining cost parameters (such as holding costs, shortage costs and set up costs) commonly used in production and inventory control models.

• be able to explain and apply quantitative models for control of single echelon inventory systems, with uncertain demand, and/or uncertain lead-times. This involves the computation of various types of service levels and expected costs, and the optimisation of control parameters like reorder points, order quantities and order-up-to levels.

• be able to explain and apply quantitative models for joint replenishments and order coordination in single echelon inventory systems.

• be able to explain and apply quantitative models for control of multi-echelon inventory systems, with uncertain demand. This involves the computation of various types of service levels and expected costs, and the optimization of control parameters like reorder points, order quantities and order-up-to levels.

• be able to explain and use quantitative methods for analysis of echelon- and installation-stock inventory control policies.

• be able to explain and use quantitative methods for lot sizing in multi-echelon systems.

• understand and be able to explain methods for coordination of supply chain systems through contracts and incentive structures.

• independently manage and solve project assignments of investigative nature with high demands on reporting/documentation of results, both in terms of oral presentations and written reports.

Skills and abilities
For a passing grade the student must

• Aggregate production planning (LP and MIP models).

• Scheduling and shop floor planning with focus on CONWIP systems (deterministic and stochastic models).

• Stochastic models for evaluation and optimization of single-echelon systems under different assumptions: continuous review, periodic review, continuous normally distributed demand, discrete compound Poisson demand, single and multi-periods, complete backordering and lost sales, service levels (S1, S2 and S3) and backorder costs, (R,Q), (S-1,S) and (s,S) systems, deterministic and stochastic lead-times (dependent and independent), uncoordinated and coordinated replenishments.

• Stochastic models for evaluation and optimization of multi-echelon (supply chain) inventory systems under different assumptions: serial and distribution systems, the METRIC approximation versus exact evaluation, (S-1,S) and (R,Q) policies, echelon-stock versus installation-stock policies, the Clark and Scarf model, lot sizing under constant and time varying demand.

• Methods, approaches and considerations for implementation of inventory and production control systems.

For a passing grade, the student must also show ability to solve investigative project assignments. This involves skills and abilities in framing and solving unstructured problems. Important aspects are problem formulation, identifying project objectives, choose appropriate methods, and performing in depth analysis. Furthermore, reporting project results requires skills in oral and written presentation techniques.

Contents
The course focuses on advanced methods for production and inventory management, particularly advanced quantitative methods for management of single- and multi-echelon production and inventory systems.

The goal is to deepen and expand the students’ knowledge in quantitative modelling of production and inventory systems both from a theoretical and applied perspective. The starting point for the content treated in the course is the theories and methods studied in the course MIO030 Production and Inventory Control. We discuss challenges associated with applying quantitative models in practice, for example, when it comes to determining cost parameters, control variables and distribution fitting.

Literature
Axsäter S. Inventory Control, Second edition. Springer, New York, 2006.
(available free of charge as e-book through the university library)
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Hopp, W. J. and M. L. Spearman, Factory Physics, third edition, Irwin McGraw-Hill, New York, 2008.
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Scientific research papers:
A1 Hopp, W.J. and M.L. Spearman (2004), “To Pull or Not to Pull: What is the Question?”, Manufacturing and Service Operations Management, Vol. 6 (Spring 2004), pp. 133-148.
A2 Spearman, M.L. and M.A. Zazanis (1992), “Push and Pull Production Systems: Issues and Comparisons”, Operations Research, Vol. 40 (3), pp 521-532.
A3 Hopp, W.J., Spearman, M.L. and I. Duenyas (1993), “Economic Production Quotas for Pull Manufacturing Systems”, IIE Transactions, Vol 25 (2), pp. 71-79.
A4 Krajewski, L.J., King, B.E., Ritzman L.P. and D.S. Wong (1987), “Kanban, MRP and Shaping the Manufacturing Environment”, Management Science, Vol. 33 (1), pp. 39-57.
A5 Spearman, M.L. and R.Q. Zhang (1999), “Optimal Lead Time Policies”, Management Science, Vol. 45 (2), pp. 290-295.
A6 Andersson J. and J Marklund (2000), “Decentralized Inventory Control in a Two-Level Distribution System”, European Journal of Operational Research, Vol. 127 (3), pp.483-506.