scholarly journals A heijunka study for the production of standard parts included in a customized finished product

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0260515
Author(s):  
Paulina Rewers ◽  
Jacek Diakun

Efficient order execution plays a crucial role in the activity of every company. In production planning it is important to find a balance between the fluctuations of orders and stability of production flow regarding the company. One of the methods of achieving this goal is heijunka (production leveling). This paper presents a study of choosing the best variant of the production planning and control system for the production of standard parts. Three variants are investigated regarding delays in order delivery. The analysis of variants was conducted using a simulation method. The method of choosing the best variant for the production system being investigated is also proposed. The results show that the best variant is a mix of production leveling and production "for stock".

2014 ◽  
Vol 1018 ◽  
pp. 563-570
Author(s):  
Marcel Wagner ◽  
Tim Schleimer ◽  
Tobias Seeberger ◽  
Gunther Reinhart

Production Planning and Control (PPC) does not only play an important role in the classical field of production. Concerning a trend to more customer related products and a so called buyers market, also the not yet strongly automated businesses have to think about topics like PPC. By forming a new automated shop floor in a commercial kitchen for example, new optimization criteria in the PPC play a crucial role. Especially in the manner of scheduling jobs different constraints concerning the handled products come up. This paper demonstrates a possibility to extend the criteria of PPC with the subjective parameter of product quality. This approach allows influencing an oven-control to reach the best product quality in its processing.


2019 ◽  
Vol 109 (05) ◽  
pp. 377-381
Author(s):  
C. Brecher ◽  
C. Fimmers ◽  
P. Blanke ◽  
S Storms ◽  
W. Herfs

In der heutigen Zeit sind durch steigende Variantenvielfalt und Individualfertigung sowie enge Lieferzeiten unterstützende IT-Systeme in der Fertigung unerlässlich. Gerade für kleine und mittlere Unternehmen (KMU) stellt dies eine Herausforderung dar, weil individuelle Schnittstellenentwicklungen und maschinenspezifische Anbindungen zeit- und kostenintensiv sind. Mit einer Produktionsplanungs- und Steuerungssystem als Integrationsplattform sowie einer allgemeingültige Schnittstelle zur Maschinenanbindung kann dem bestehenden Handlungsbedarf entsprochen werden.   Nowadays, due to the increasing variety of variants and individual production as well as tight delivery times, supporting IT systems are indispensable in production. This poses a particular challenge for SMEs, since individual interface developments and machine-specific connections are time-consuming and costly. These challenges can be met by using a Production Planning and Control system as an integration platform and a generally valid interface to the machine connection.


Procedia CIRP ◽  
2019 ◽  
Vol 81 ◽  
pp. 1195-1200
Author(s):  
Alexander Zipfel ◽  
Stefan Braunreuther ◽  
Gunther Reinhart

Author(s):  
Olumide Emmanuel Oluyisola ◽  
Swapnil Bhalla ◽  
Fabio Sgarbossa ◽  
Jan Ola Strandhagen

AbstractIn furtherance of emerging research within smart production planning and control (PPC), this paper prescribes a methodology for the design and development of a smart PPC system. A smart PPC system uses emerging technologies such as the internet of things, big-data analytics tools and machine learning running on the cloud or on edge devices to enhance performance of PPC processes. It achieves this by using a wider range of data sources from the production system, capturing and utilizing the experience of production planners, using analytics and machine learning to harness insights from the data and allowing dynamic and near real-time action to the continuously changing production system. The proposed methodology is illustrated with a case study in a sweets and snacks manufacturing company, to highlight the key considerations and challenges production managers might face during its application. The case further demonstrates considerations for scalability and flexibility via a loosely coupled, service-oriented architecture and the selection of fitting algorithms respectively to address a business requirement for a short-term, multi-criteria and event-driven production planning and control solution. Finally, the paper further discusses the challenges of PPC in smart manufacturing and the importance of fitting smart technologies to planning environment characteristics.


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