scholarly journals Labor flexibility integration in workload control in Industry 4.0 era

2021 ◽  
Author(s):  
Federica Costa ◽  
Alberto Portioli-Staudacher
Keyword(s):  
Production Planning ◽  
Industry 4.0 ◽  
Shop Floor ◽  
Production Planning And Control ◽  
Labor Flexibility ◽  
Planning And Control ◽  
Workload Control ◽  
Low Volume ◽  
And Control ◽  
The Impact

AbstractThe paradigm shift toward Industry 4.0 is facilitating human capability, and at the center of the research are the workers—Operator 4.0—and their knowledge. For example, new advances in augmented reality and human–machine interfaces have facilitated the transfer of knowledge, creating an increasing need for labor flexibility. Such flexibility represents a managerial tool for achieving volume and mix flexibility and a strategic means of facing the uncertainty of markets and growing global competition. To cope with these phenomena, which are even more challenging in high-variety, low-volume contexts, production planning and control help companies set reliable due dates and shorten lead times. However, integrating labor flexibility into the most consolidated production planning and control mechanism for a high-variety, low-volume context—workload control—has been quite overlooked, even though the benefits have been largely demonstrated. This paper presents a mathematical model of workload control that integrates labor flexibility into the order review and release phase and simulates the impact on performance. The main results show that worker transfers occur when they are most needed and are minimized compared to when labor flexibility is at a lower level of control—shop-floor level—thus reducing lead time.

Product-Quality Based Scheduling of Automated Food Processing

2014 ◽  
Vol 1018 ◽  
pp. 563-570
Author(s):  
Marcel Wagner ◽  
Tim Schleimer ◽  
Tobias Seeberger ◽  
Gunther Reinhart
Keyword(s):  
Product Quality ◽  
Production Planning ◽  
Food Processing ◽  
Crucial Role ◽  
Classical Field ◽  
Shop Floor ◽  
Production Planning And Control ◽  
Optimization Criteria ◽  
Planning And Control ◽  
And Control

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.

scholarly journals The concept of operation and production control

2021 ◽  
Vol 27 (2) ◽  
pp. 100-107
Author(s):  
Radosław Wolniak
Keyword(s):  
Artificial Intelligence ◽  
Production Planning ◽  
Industry 4.0 ◽  
Production Management ◽  
Production Control ◽  
Main Function ◽  
Production Planning And Control ◽  
Factors Affecting ◽  
Planning And Control ◽  
And Control

Abstract The theoretical aim of the paper is to analyses the main function and concept of production control in operation management. The empirical aim of the paper is to investigate polish production firm opinion about factors affecting production planning and control and also functions of production planning and control. Production control is very important in every factory, and every aspect of operation and production management especially in times of Industry 4.0 conditions. In the paper we presented all classical seven task of production management control. Also there is in the paper an analysis of main factors affecting production control in industrial organization. In the paper we analysed the problems connected with production control. Nowadays in the conditions of Industry 4.0 this is very important concept because the increasing level of digitalization of all industrial processes leads to possibility of detailed analysis of all processes and better level of control. Operation managers should have good level of knowledge about production control and especially quality control. They can use in this many new information tools like statistical methods and artificial intelligence. Especially we think that in the future many function of production control would be assisted by artificial intelligence. We also in the paper give results of research conducted on example of 30 polish production organizations located in Silesia region.

scholarly journals Teaching-Learning Strategies to Production Planning and Control Concepts: Application of Scenarios to Sequencing Production with Virtual Reality Support

2021 ◽  
Vol 20 (8) ◽  
pp. 108-125
Author(s):  
Fernando Elemar Vicente dos Anjos ◽  
Luiz Alberto Oliveira Rocha ◽  
Rodrigo Pacheco ◽  
Débora Oliveira da Silva
Keyword(s):  
Virtual Reality ◽  
Production Planning ◽  
Learning Strategies ◽  
Production Planning And Control ◽  
Production Engineering ◽  
Planning And Control ◽  
Process Manufacturing ◽  
Teaching Learning ◽  
And Control ◽  
The Impact

This paper aims to present scenarios to be applied in higher education to the theme of production planning and control, addressing factors of the production system and indicators arising from this process and the application of virtual reality to support the process. The applied method combines the development of six scenarios for virtual reality application and the discussion about the impacts in indicators from the production planning and control, for example, inventory in the process, manufacturing lead-time, use of equipment, and punctual delivery attendance. Findings revealed that the teaching-learning process of production planning and control, when applied through scenarios, generates opportunities for students to learn the impact in the indicators. The virtual reality in this environment supports creating differentiated teaching-learning environments to generate the most significant knowledge for students which positively impacts the future in the world of work. In addition, it allows people involved in the teaching-learning processes of production engineering to apply the concepts presented in the sequencing process, lean about the impacts of decisions on production sequencing indicators and appreciate the support of virtual reality to generate an environment more cognitive for students.

scholarly journals The Influence of Cognitive Biases in Production Planning and Control: Considering the Human Factor for the Design of Decision Support Systems

2021 ◽  
Author(s):  
Julia Bendul ◽  
Melanie Zahner
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Production Planning ◽  
Cognitive Biases ◽  
Production Planning And Control ◽  
Due Date ◽  
Planning And Control ◽  
Human Decision ◽  
And Control ◽  
The Impact

Production planning and control (PPC) requires human decision-making in several process steps like production program planning, production data management, and performance measurement. Thereby, human decisions are often biased leading to an aggravation of logistic performance. Exemplary, the lead time syndrome (LTS) shows this connection. While production planners aim to improve due date reliability by updating planned lead times, the result is actually a decreasing due date reliability. In current research in the field of production logistics, the impact of cognitive biases on the decision-making process in production planning and control remains at a silent place. We aim to close this research gap by combining a systematic literature review on behavioral operation management and cognitive biases with a case study from the steel industry to show the influence of cognitive biases on human decision-making in production planning and the impact on logistic performance. The result is the definition of guidelines considering human behavior for the design of decision support systems to improve logistic performance.

Workload Control

2015 ◽  
pp. 61-69
Author(s):  
Nuno O. Fernandes
Keyword(s):  
Production Planning ◽  
Performance Criteria ◽  
Production Planning And Control ◽  
Manufacturing Enterprises ◽  
Planning And Control ◽  
Processing Times ◽  
Workload Control ◽  
Sources Of Variation ◽  
Demand Variability ◽  
And Control

Global competition and changing customer requirements are putting major challenges in the production planning and control systems of manufacturing enterprises. Production planning and control requires robust methods able to cope with demand variability, processing times variability, routing sequences, resource availability, etc., between other sources of variation. Production planning and control significantly influences target performance criteria such as the delivery time, on-time delivery, work-in-process inventory, and resources utilization. Therefore, production planning and control is strategically important for the economic success of these enterprises and innovative production planning and control methods are required. This chapter describes how workload control, a leading production planning and control system for small- and medium-sized enterprises, operates and illustrates how it aids in shortening and stabilising throughput times based on a simulation study of a small made-to-order production system.

Machine learning applied in production planning and control: a state-of-the-art in the era of industry 4.0

2020 ◽  
Vol 31 (6) ◽  
pp. 1531-1558 ◽  
Author(s):  
Juan Pablo Usuga Cadavid ◽  
Samir Lamouri ◽  
Bernard Grabot ◽  
Robert Pellerin ◽  
Arnaud Fortin
Keyword(s):  
Machine Learning ◽  
Production Planning ◽  
Industry 4.0 ◽  
State Of The Art ◽  
Production Planning And Control ◽  
Planning And Control ◽  
And Control
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