A method for assessing pull production systems: a study of manufacturing, healthcare, and construction

2020 ◽  
pp. 1-21 ◽  
Author(s):  
Bruna Dones Gayer ◽  
Tarcisio Abreu Saurin ◽  
Priscila Wachs
Keyword(s):  
Production Systems ◽  
Pull Production

System dynamics modelling of fixed and dynamic Kanban controlled production systems: a supply chain perspective

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jagan Mohan Reddy K. ◽  
Neelakanteswara Rao A. ◽  
Krishnanand Lanka ◽  
PRC Gopal
Keyword(s):  
Supply Chain ◽  
System Dynamics ◽  
Cycle Time ◽  
Production System ◽  
Demand Uncertainty ◽  
Production Systems ◽  
Decision Variable ◽  
Content Type ◽  
Pull Production ◽  
Kanban System

Purpose Pull production systems have received much attention in the supply chain management environment. The number of Kanbans is a key decision variable in the pull production system as it affects the finished goods inventory (FGI) and backorders of the system. The purpose of this study is to compare the performance of the fixed and dynamic Kanban systems in terms of operational metrics (FGI and backorders) under the demand uncertainty. Design/methodology/approach In this paper, the system dynamics (SD) approach was used to model the performance of fixed and dynamic Kanban based production systems. SD approach has enabled the feedback mechanism and is an appropriate tool to incorporate the dynamic control during the simulation. Initially, a simple Kanban based production system was developed and then compared the performance of production systems with fixed and dynamic controlled Kanbans at the various demand scenarios. Findings From the present study, it is observed that the dynamic Kanban system has advantages over the fixed Kanban system and also observed that the variation in the backorders with respect to the demand uncertainty under the dynamic Kanban system is negligible. Research limitations/implications In a just-in-time production system, the number of Kanbans is a key decision variable. The number of Kanbans is mainly depended on the demand, cycle time, safety stock factor (SSF) and container size. However, this study considered only demand uncertainty to compare the fixed and dynamic Kanban systems. This paper further recommends researchers to consider other control variables which may influence the number of Kanbans such as cycle time, SSF and container size. Originality/value This study will be useful to decision-makers and production managers in the selection of the Kanban systems in uncertain demand applications.

Customer Service in Pull Production Systems

1992 ◽  
Vol 40 (5) ◽  
pp. 948-958 ◽  
Author(s):  
Mark L. Spearman
Keyword(s):  
Customer Service ◽  
Production Systems ◽  
Pull Production

Pull Production Systems

2021 ◽  
pp. 80-112
Author(s):  
Eduardo Guilherme Satolo ◽  
Milena Estanislau Diniz Mansur dos Reis ◽  
Robisom Damasceno Calado
Keyword(s):  
Decision Making ◽  
Hybrid Systems ◽  
Production System ◽  
Lean Manufacturing ◽  
Production Systems ◽  
Pull Production ◽  
Decision Making Processes ◽  
Pull Systems ◽  
Aid Decision ◽  
Pull Production System

This chapter aims to organize knowledge about pull production systems by presenting the underlying concepts of lean manufacturing as for its origin, principles, and relations with PPC. Pull production is one the fundamental principles of lean manufacturing, and its implementation can bring positive impacts. For such a purpose, sequential and mixed supermarket pull systems stand out in which the integration between pull production systems and PPC and its various levels is a main subject of discussion. The JIT model or Kanban method and hybrid systems, such as conwip and lung-drum-string theory, are mechanisms for managing pull production systems. Finally, a pull production system implementation is presented for illustration purposes. At the end of this chapter, it is expected that skills are developed by readers, which are going to assist them in using the tools presented to model production systems and aid decision-making processes.

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