Autonomous Production Control Methods - Job Shop Simulations

Die situationsabhängige Steuerung produktionslogistischer Prozesse ist im Kontext von Industrie 4.0 von zunehmender Bedeutung. Dem steht in der Praxis die Anforderung der Einhaltung zentraler Planvorgaben entgegen. In diesem Fachbeitrag wird simulationsbasiert der Einfluss der Planorientierung autonomer und konventioneller Fertigungssteuerungsverfahren auf die Erreichung logistischer und planerischer Ziele unter dynamischen Bedingungen untersucht, wobei eine detaillierte Betrachtung der Termintreue erfolgt.   The situation-dependent control of production logistics processes is of increasing relevance in the context of Industrie 4.0 (Integrated Industry). However, it is also important in industrial practice to stick to arranged production schedules. Therefore, this article examines the influence of schedule-orientation of production control methods on logistic performance and schedule adherence under dynamic circumstances paying particular attention to the adherence to due dates.

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Comparative study of autonomous production control methods using simulation

Simulation Modelling Practice and Theory ◽

10.1016/j.simpat.2020.102142 ◽

2020 ◽

Vol 104 ◽

pp. 102142

Author(s):

Luís Miguel Martins ◽

Nuno Octávio Garcia Fernandes ◽

Maria Leonilde Rocha Varela ◽

Luís Miguel Silva Dias ◽

Guilherme Augusto Borges Pereira ◽

...

Keyword(s):

Comparative Study ◽

Production Control ◽

Control Methods

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Rapid reconfiguration of job shop production control system based on soft components technology

The International Journal of Advanced Manufacturing Technology ◽

10.1007/s00170-005-0149-z ◽

2006 ◽

Vol 30 (11-12) ◽

pp. 1154-1164 ◽

Cited By ~ 3

Author(s):

Feng Liang ◽

Zhibin Jiang ◽

Richard Y. K. Fung ◽

Liyan Tao ◽

Mingchen Ma

Keyword(s):

Control System ◽

Production Control ◽

Job Shop ◽

Production Control System

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Implementation of hybrid Kanban-CONWIP system: a case study

Journal of Manufacturing Technology Management ◽

10.1108/jmtm-03-2016-0043 ◽

2017 ◽

Vol 28 (6) ◽

pp. 714-736 ◽

Cited By ~ 11

Author(s):

Dênis Gustavo Leonardo ◽

Bruno Sereno ◽

Daniel Sant Anna da Silva ◽

Mauro Sampaio ◽

Alexandre Augusto Massote ◽

...

Keyword(s):

Control Systems ◽

Hybrid System ◽

Production Control ◽

Job Shop ◽

Lean Production ◽

Shop Floor ◽

Content Type ◽

Floor Control ◽

Low Volume

Purpose Shop floor control systems are generally major points of discussion in production planning and control literature. The purpose of this paper is to investigate how lean production control principles can be used in a make-to-order (MTO) job shop, where the volume is typically low and there is high variety. This paper examines the procedures involved in implementing a constant work-in-process (CONWIP)/Kanban hybrid system in the shop floor environment and also provides insights and guidelines on the implementation of a hybrid system in a high-variety/low-volume environment. Design/methodology/approach The authors review literature on Kanban, CONWIP, and CONWIP/Kanban hybrid systems to analyze how lean production control principles can be used in a MTO job shop. The second part focuses on the process of implementation. Using a case study of a manufacturer of electromechanical components for valve monitoring and controls, the paper describes how the operation is transformed by for more efficient shop floor control systems. Real experiments are used to compare pre- and post-improvement performance. Findings The study shows that the proposed hybrid Kanban-CONWIP system reduced the cycle time and achieved an increase of 38 percent in inventory turnover. The empirical results from this pilot study provide useful managerial insights for a benchmarking analysis of the actions to be taken into consideration by companies that have similar manufacturing systems. Research limitations/implications The statistic generalization of the results is impossible due to the use of a single case method of study. Originality/value This paper provides insights and guidelines on the implementation of a hybrid system in a high-variety/low-volume environment. The literature on real applications of hybrid CONWIP/Kanban by case study is limited.

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Production events graphical deduction model enabled real-time production control system for smart job shop

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science ◽

10.1177/0954406217728531 ◽

2017 ◽

Vol 232 (16) ◽

pp. 2803-2820 ◽

Cited By ~ 4

Author(s):

Chuang Wang ◽

Pingyu Jiang ◽

Tiantian Lu

Keyword(s):

Control System ◽

Real Time ◽

Production Control ◽

Job Shop ◽

Material Flows ◽

Time Production ◽

Production Control System ◽

Work In Process ◽

Control Procedures ◽

Manufacturing Resources

Under industry 4.0, the production control system of smart job shop should be able to real-time respond to various production events and effectively coordinate different kinds of manufacturing resources in good order according to their material flows. Production events enabled real-time production control system is good at responsibility and flexibility. Internet of things (IoT) can provide enormous real-time production events, which represent the change of material flows. However, some of production events seriously interfere with production control procedures. They sharply restrict the real-time capability of production control system. Thus, it is imperative that an efficient realization method of production control system, which is enabled by useful production events. Additionally, the control system should satisfy production control procedures visibility. For solving the problems, a production events graphical deduction model enabled real-time production control system for smart job shop is proposed in this article. Firstly, the manufacturing resources are divided into work in process related, operator-related, cutting tool-related, fixture tool-related, and measuring tool-related. And the material flows of different manufacturing resources in IoT-enabled smart job shop are described in detail. Secondly, the graphical deduction model of production event is put forward. Based on the model, the material flows of manufacturing resources in a process are segmented into several stages according to different production events. And then, the cooperation model of manufacturing resources is established by using the time and logical relationships between production events. Thirdly, the control model in a process is drawn from the cooperation model. Next, the entire control procedure of work in process production in IoT-enabled smart job shop is proposed. Finally, a small-scale IoT-enabled manufacturing system is used to verify the feasibility of the proposed model and methods.

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