Thesis for the Degree of Licentiate of Engineering

An advanced planning and scheduling (APS) systems is defined as any computer program that uses advanced mathematical algorithms or logic to perform optimization, and/or simulation on finite capacity scheduling, sourcing, capital planning, resource planning, forecasting, demand planning and others. The expectations of APS systems have been high, both from academia and industry in the subject area of manufacturing planning and control. Relative the massive interest there has not been much written about how APS systems are used in practice and what effects an APS approach really results in. This thesis focuses on the use of APS systems in manufacturing planning and control (MPC) processes, and the research questions is to explore how APS can support these processes, which benefits that can be achieved and which prerequisites to consider when using APS systems. Three case studies have been conducted including seven case companies that use APS in different MPC processes. The results are presented in four appended papers. Empirical data from the case studies have mainly been conducted thorough interviews with actors involved in MPC processes. The literature review and the case study analyses have generated frameworks describing how APS systems could support the activities in sales and operations planning (S&OP) and production activity control (PAC). A framework was also developed for when to use APS systems in S&OP processes. Three different types of benefits were identified when using APS systems in MPC processes; (1) decision support, (2) planning efficiency, and (3) learning effects. The prerequisites which may affect the probability of conversion success where separated into prerequisites identified in the selection phase, in the implementation phase, and in the post-implementation phase. Examples of prerequisites identified in the different phases were; the aim of the process, complexity in planning task, the design of the model, access to and quality of planning data, the capabilities of the APS system, the use of APS, user characteristics, planning organization, system support, system acceptance, and high discipline of users. The thesis has contributed with increased knowledge for the use of APS system in the MPC processes. In particular the definitions in the thesis, the identified variables, and the frameworks should be of interest for researcher, management, and consultants in the area of manufacturing planning and control.