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2016, vol. 11, iss. 2, pp. 235-243
Proof obligations as a support tool for efficient process management in the field of production planning and scheduling
Tomas Bata University in Zlin, Faculty of Management and Economics, Department of Industrial Engineering and Information Systems, Czech Republic
This paper is one of contribution to the RVO project: Modelling of effective production and administration processes parameters in industrial companies based on concept Industry 4.0, realized by Department of Industrial Engineering and Information Systems, Faculty of Management and Economics, Tomas Bata University in Zlin

Production planning and scheduling is one of the most important business processes that significantly influence the performance of manufacturing companies. There are many information systems supporting production planning and scheduling and some of them are based on very sophisticated planning algorithms. Despite this fact, many companies still face serious problems even while using professional software tools for production planning and scheduling. Obviously, a lot of other changes in form of process innovations are required. This paper deals with the problem of process management in the field of production planning and scheduling. Our study explains reasons for low performance of advanced technologies and provides solution in form of system model of key factors affecting the efficiency of planning software. Research part is based on the study conducted within Czech manufacturing companies in form of questionnaire-based investigation combined with interviews. Proposed solution is extended to the abstract mathematical model based on proof obligations which prove or disprove the correctness of intended algorithms. Our study provides basic example of such an abstract model and describes its functionality and influence to proper production planning and scheduling. It will be processed to the form of complex expert system based on Event B method in the future.
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article language: English
document type: Original Paper
DOI: 10.5937/sjm11-11135
published in SCIndeks: 27/10/2016
peer review method: double-blind
Creative Commons License 4.0

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