Multi-assortment rhythmic production planning and control

Skołud, B.; Krenczyk, Damian; Zemczak, Marcin

doi:10.1088/1757-899x/95/1/012133

Cited by 13 publications

(2 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…One of the methods that can contribute to solve these problems is the use of discrete-event simulation system as a tool for verification, analysis and optimization of processes flow plans [1,2,4,6]. Execution of calculations for each production flow variant may be successfully supported by the use of discrete-event simulation models for dynamic production networks.…”

Section: Production Planning In Virtual and Dynamic Manufacturing Netmentioning

confidence: 99%

“…One such area of computer support witch allow to increase the efficiency of production planning process is computer modelling, simulation and visualization of production flow [1,2]. Conducted research were oriented towards growth the efficiency of production planning and control systems through their integration with computer discrete event modelling, simulation and visualization systems for multi-assortment manufacturing systems [1,2,3,4,5,6,7,8]. Possibilities of using the methodology of semi-automatic model generation based on parametric approach for supporting processes of production planning is presented.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Semi-automatic simulation model generation of virtual dynamic networks for production flow planning

Krenczyk

Skołud

Olender

2016

IOP Conf. Ser.: Mater. Sci. Eng.

Self Cite

View full text Add to dashboard Cite

Abstract. Computer modelling, simulation and visualization of production flow allowing to increase the efficiency of production planning process in dynamic manufacturing networks. The use of the semi-automatic model generation concept based on parametric approach supporting processes of production planning is presented. The presented approach allows the use of simulation and visualization for verification of production plans and alternative topologies of manufacturing network configurations as well as with automatic generation of a series of production flow scenarios. Computational examples with the application of Enterprise Dynamics simulation software comprising the steps of production planning and control for manufacturing network have been also presented. IntroductionIn the area of organizational production preparation the modules of MRP I, MRP II and scheduling systems are mainly used. Unfortunately, in most cases, modules supporting the processes of production flow planning do not include all constrains of the production system, for instance constrains related to internal and external logistics. In order to fully verify prepared production plans, the following must be analysed: available quantities and capacity of transport means, possible risks of collisions, storage location and capacity (inter-operational, input, output) and their impact on the opportunities to meet the planned production norms. It is necessary to search for computer aided decision-making tools and implement them in planning process. One such area of computer support witch allow to increase the efficiency of production planning process is computer modelling, simulation and visualization of production flow [1,2]. Conducted research were oriented towards growth the efficiency of production planning and control systems through their integration with computer discrete event modelling, simulation and visualization systems for multi-assortment manufacturing systems [1,2,3,4,5,6,7,8]. Possibilities of using the methodology of semi-automatic model generation based on parametric approach for supporting processes of production planning is presented. Simulation models are generated based on simulation atoms (building blocks) stored in simulation libraries along with a fixed production routes (static data), and sequencing control of processes flow data for manufacturing resources (dynamic data). Proposed approach allows to eliminate the problems related to the preparation of simulation model in the traditional way, i.e. labour-intensive and time-consuming. The research on methodology of semi-automatic models generation presented in this paper includes issues related to the area of Virtual Enterprises (VE), Virtual Manufacturing Network (VMN) and Dynamic

show abstract

Section: Production Planning In Virtual and Dynamic Manufacturing Netmentioning

confidence: 99%