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Advanced planning and scheduling systems in manufacturing planning and control processes
No full textAdvanced planning and scheduling systems in manufacturing planning and control processes
No full text
The potential benefits of advanced planning and scheduling systems in sales and operations planning
No full textPurpose – The purpose of this paper is to explore what potential benefits may be achieved by using
advanced planning and scheduling (APS) systems in the sales and operations planning (S&OP) process.
Design/methodology/approach – The paper investigates benefits at the S&OP process level by
interviewing APS experts and APS users. Several methods have been used; literature review, Delphi
study, and a case study at a company in the chemical industry which uses APS system support in the
S&OP process.
Findings – Three types of potential benefits were found to be achieved when using APS systems in the
S&OP process; benefits concerning decision support, planning efficiency and learning effects. The most
common type was decision support benefits according to APS users and APS experts. The results from
the case company showed that the benefits perceived in the different S&OP activities differed. In the
activities concerning the preparation and generation of delivery plans, the perceived benefits mainly
concerned learning effects. In the activities concerning the generation of a production plan, the benefits
were foremost found in planning efficiency. In the S&OP meeting decision support benefits were highest
valued. The reason for the different results can be explained by the aim of the activity, how APS was
used in the activity, the user characteristics and the design of the model and access and quality of
planning data.
Research limitations/implications – The focus of this paper is on potential benefits of APS
systems in the S&OP process only, not the costs. It has established a typology of potential benefits. No
validation in form of statistical analysis has been done. The empirical analysis is mainly based on
findings from a single case study.
Practical implications – The findings about the types of APS potential will assist companies in
understanding the benefits they can expect from its use in the S&OP process. The case study analysis
gives further insight into how APS can be employed and what benefits different APS user categories can
expect when it is used in an appropriate way.
Originality/value – The knowledge about which benefits that can be achieved when using APS in
the S&OP process is quite unexplored. This paper fills some of these gaps
Improving performance with sophisticated master production scheduling
No full textLiterature addressing master production scheduling (MPS) typically focuses on the development of sophisticated MPS methods with the expectation that these methods will result in feasible plans and improved performance. However, empirical evidence showing that sophisticated methods are better than simpler ones remains scarce, and companies have reported difficulties with using sophisticated planning methods. In this study, we therefore investigate how sophisticated MPS methods impact three perception-based performance variables—namely, plan feasibility, inventory turnover rate, and delivery service—while accounting for the complexities of planning environments and MPS maturity. We define six MPS methods, ranging from those that ignore capacity to those exhibiting capacity-constrained planning using optimisation. An analysis of survey data from a sample of Swedish manufacturing companies reveals a significant negative effect of less sophisticated methods compared to highly sophisticated ones in terms of plan feasibility, as well as a significant negative effect of the simplest method in considering available capacity compared to highly sophisticated methods in terms of delivery service. The maturity of the MPS process most significantly impacts all performance measures, whereas planning environment complexity shows only a weak negative impact. Findings also indicate that both MPS process maturity and sophisticated MPS methods mediate the negative performance prompted by complex planning environments. Results thus suggest that sophisticated MPS may generally affect performance both directly and indirectly. Using sophisticated MPS methods reduces the negative effects of complex planning environments and results in more feasible plans irrespective of environment complexity and process maturity
Linking master production scheduling performance to planning methods
No full textThe purpose is to explain how the planning environment, process maturity and data quality affect the capability of the planning method to provide high MPS performance. The analysis conducted with survey data from a sample of Swedish manufacturing companies shows that the process maturity and data quality are very important for successfully using planning methods. The data quality is shown especially important for simple planning methods whereas the MPS process maturity was particular important when using advanced planning methods. The complexity in the planning environment did not seem to influence the successful use of planning methods and MPS performance
Linking master production scheduling performance to planning methods
No full textThe purpose is to explain how the planning environment, process maturity and data quality affect the capability of the planning method to provide high MPS performance. The analysis conducted with survey data from a sample of Swedish manufacturing companies shows that the process maturity and data quality are very important for successfully using planning methods. The data quality is shown especially important for simple planning methods whereas the MPS process maturity was particular important when using advanced planning methods. The complexity in the planning environment did not seem to influence the successful use of planning methods and MPS performance
A comparison of schedules resulting from priority rules and mathematical optimization for a real production cell [Elektronisk resurs]
No full textIn this article we present a complete algorithm using mathematical optimization tools for solving a flexible job shop scheduling problem at Volvo Aero, a company producing high-valued low volume components for the aircraft industry. The goal of the scheduling is to facilitate a higher utilization of the cell while minimizing the total tardiness and the cell throughput time. The production cell consists of ten resources (machines and workstations) whereof five are multipurpose machines that can carry out a variety of operations; the so-called multitask machines work in parallel instead of one dedicated machine for each product. The production cell is studied from a mathematical as well as a logistical point of view. The quality of the schedules is measured by means of the total tardiness and computation time. The resulting schedules from a mathematical optimization model are compared with schedules generated by priority rules, which are similar to today’s manual scheduling of the multitask cell. The tests were carried out for different realistic scenarios with regard to work load and product mix. The resulting schedules, which as expected outperformed the two commonly used priority rules, are obtained within minutes for the upcoming shift
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