Abstract
The article deals with the design of an innovative system for scheduling piece and small series discrete production using a combination of parametric simulation models and selected optimization methods. An innovative system for solving production scheduling problems is created based on data from a real production system at the workshop level. The methodology of the innovative system using simulation and optimization methods deals with the sequential scheduling problem due to its versatility, which includes several production systems and due to the fact that in practice, several modifications to production scheduling problems are encountered. Proposals of individual modules of the innovative system with the proposed communication channels have been presented, which connect the individual elements of the created library of objects for solving problems of sequential production scheduling. With the help of created communication channels, it is possible to apply individual parameters of a real production system directly to the assembled simulation model. In this system, an initial set of optimization methods is deployed, which can be applied to solve the sequential problem of production scheduling. The benefit of the solution is an innovative system that defines the content of the necessary data for working with the innovative system and the design of output reports that the proposed system provides for production planning for the production shopfloor level. The DPSS system works with several optimization methods (CR—Critical Ratio, S/RO—Slack/Remaining Operations, FDD—Flow Due Date, MWKR—Most Work Remaining, WSL—Waiting Slack, OPFSLK/PK—Operational Flow Slack per Processing Time) and the simulation experiments prove that the most suitable solution for the FT10 problem is the critical ratio method in which the replaceability of the equipment was not considered. The total length of finding all solutions by the DPSS system was 1.68 min. The main benefit of the DPSS system is the combination of two effectively used techniques not only in practice, but also in research; the mentioned techniques are production scheduling and discrete computer simulation. By combining techniques, it is possible to generate a dynamically and interactively changing simulated production program. Subsequently, it is possible to decide in the emerging conditions of certainty, uncertainty, but also risk. To determine the conditions, models of production systems are used, which represent physical production systems with their complex internal processes. Another benefit of combining techniques is the ability to evaluate a production system with a number of emerging problem modifications.
Highlights
From the realized knowledge and study of the researched area [1,2,3], the potential in the problem of sequential production scheduling (JSSP) was found because its versatility includes several manufacturing companies and at the same time because it is possible to meet several modifications to scheduling problems in practice, for example, the selection of machines, limited quantities of intermediate warehouses, etc
Fictitious production system—an exampleisisaasolution solutiontotothe themost mostwidely widelyused used problem of sequential production scheduling, which is compiled in the range of 10 × 10 problem of sequential production scheduling, which is compiled in the range of 10 × 10
Each of the acquired production schedules consisted of various incoming orders, while the indicators were monitored during the evaluation, which decided how the individual indicators in the sanction function changed by the set control rule
Summary
From the realized knowledge and study of the researched area [1,2,3], the potential in the problem of sequential production scheduling (JSSP) was found because its versatility includes several manufacturing companies and at the same time because it is possible to meet several modifications to scheduling problems in practice, for example, the selection of machines, limited quantities of intermediate warehouses, etc. Orders that are released in production must be translated into tasks with appropriate deadlines. These tasks must be processed using the available resources in the given order or sequence. It is necessary to consider unforeseen events in the workshop such as machine failures or longer processing times than expected, as they can have a major impact on schedules. In such an environment, developing a detailed schedule of tasks helps maintain efficiency and control of operations [8]
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