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.

Die synchrone Produktion*/Synchronous manufacturing - An approach for semi-autonomous production planning and control and human-based decision support

2015 ◽  
Vol 105 (04) ◽  
pp. 204-208
Author(s):  
D. Kreimeier ◽  
E. Müller ◽  
F. Morlock ◽  
D. Jentsch ◽  
H. Unger ◽  
...  
Keyword(s):  
Decision Support ◽  
Real Time ◽  
Production Planning ◽  
Data Exchange ◽  
Production Control ◽  
Production Planning And Control ◽  
Planning And Control ◽  
Manufacturing Execution Systems ◽  
And Control ◽  
Manufacturing Execution

Kurzfristige sowie ungeplante Änderungen – wie Auftragsschwankungen, Maschinenausfälle oder Krankheitstage der Mitarbeiter – beeinflussen die Produktionsplanung und -steuerung (PPS) von Industriefirmen. Trends wie Globalisierung und erhöhter Marktdruck verstärken diese Probleme. Zur Komplexitätsbewältigung bei der Entscheidungsfindung zur Fertigungssteuerung kommen in der Produktion Werkzeuge der „Digitalen Fabrik“, beispielsweise Simulationsprogramme, oder IT (Informationstechnologie)-Lösungen, wie Manufacturing Execution Systems (MES), zum Einsatz. Eine Verknüpfung dieser Bereiche würde einen echtzeitfähigen Datenaustausch erlauben, der wiederum eine echtzeitfähige Entscheidungsunterstützung bietet. Der Fachbeitrag stellt hierfür einen Lösungsansatz vor.   Sudden and unsystematic changes, such as fluctuations in order flow, machine failures, or employee sick days affect the Production Planning and Control (PPC) activities of industrial companies. Trends like globalization and increased market pressure intensify these problems. To master the complexity of decision-making in production control, tools of the digital factory (e.g. simulation systems) or IT systems (e.g. Manufacturing Execution Systems (MES)) are applied in manufacturing. Combining these areas would enable real-time capable data exchange which, in turn, provides real-time capable decision support. This article presents an approach for solving this problem.

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.

Using Discrete-Event Simulation Systems as Support for Production Planning

2015 ◽  
Vol 809-810 ◽  
pp. 1456-1461 ◽  
Author(s):  
Damian Krenczyk ◽  
Malgorzata Olender
Keyword(s):  
Decision Making ◽  
Production Planning ◽  
Production Management ◽  
New Technologies ◽  
Discrete Event ◽  
Simulation Program ◽  
High Tech ◽  
Production Planning And Control ◽  
Planning And Control ◽  
And Control

In the days of fierce competition, rapid changes and new technologies, production, and above all, production planning and control cannot be implemented in isolation to changes in the market. The ability to quickly adjust to changes, being flexible is now essential for high tech companies. One of the key area of production management, that must continuously evolve by searching for new methods and tools for increasing the efficiency of decision-making process is the area of production planning and control. In solving the problems associated with production planning are increasingly used advanced simulation programs. They support the planners, especially in situations related to changes in the assortment, or the introduction of new products into the market. A practical example of using the simulation program for production planning is presented in the paper. It is shown that an advanced simulation program can be an effective tool used in decision making area. The construction of the model, and performed experiments are crucial for enterprises where among other things punctuality and flexibility are the most important elements. A short time for the results of the simulation allows for quick response and, if necessary, make changes to the model by planners to achieve the best results with the given parameters associated with the required to complete the production orders.

Increasing data integrity for improving decision making in production planning and control

CIRP Annals ◽  
2017 ◽  
Vol 66 (1) ◽  
pp. 425-428 ◽  
Author(s):  
Günther Schuh ◽  
Christina Reuter ◽  
Jan-Philipp Prote ◽  
Felix Brambring ◽  
Julian Ays
Keyword(s):  
Decision Making ◽  
Production Planning ◽  
Data Integrity ◽  
Production Planning And Control ◽  
Planning And Control ◽  
And Control

Production Planning and Control in an Automobile Closed-Loops Assembly Line

2012 ◽  
Vol 502 ◽  
pp. 103-108
Author(s):  
L.P. Ferreira ◽  
E. Ares ◽  
G. Peláez ◽  
B. Tjahjono ◽  
J.J. Areal
Keyword(s):  
Decision Making ◽  
Assembly Line ◽  
Real Problem ◽  
Production Planning And Control ◽  
Network Configuration ◽  
Closed Loops ◽  
Planning And Control ◽  
Automobile Assembly ◽  
And Control ◽  
The Impact

The work presented in this paper consists of the development of a decision making support system, based on a real problem, with the purpose of optimizing the operation of an automobile assembly line with a four closedloop network configuration. This layout system reflects one of the most common configurations of automobile assembly and preassembly lines formed by conveyors. The impact of the speed variation of the intermediate buffers formed by conveyors on the first three closed-loops and of the proportion of four-door car bodies on the number of cars produced / hour has been thoroughly investigated.

scholarly journals Decision Aiding to Overcome Biases in Object Identification

2012 ◽  
Vol 2012 ◽  
pp. 1-7 ◽  
Author(s):  
Mary Fendley ◽  
S. Narayanan
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Cognitive Biases ◽  
Target Identification ◽  
Object Identification ◽  
Identification Accuracy ◽  
Human Decision ◽  
The Impact

Human decision makers typically use heuristics under time-pressured situations. These heuristics can potentially degrade task performance through the impact of their associated biases. Using object identification in image analysis as the context, this paper identifies cognitive biases that play a role in decision making. We propose a decision support system to help overcome these biases in this context. Results show that the decision support system improved human decision making in object identification, including metrics such as time taken to identify targets in an image set, accuracy of target identification, accuracy of target classification, and quantity of false positive identification.

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