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 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.

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.

Simulation of a Closed-Loops Assembly Line

2012 ◽  
Vol 502 ◽  
pp. 127-132 ◽  
Author(s):  
L.P. Ferreira ◽  
E. Ares ◽  
G. Peláez ◽  
A. Resano ◽  
C.J. Luis-Pérez ◽  
...  
Keyword(s):  
Assembly Line ◽  
Closed Loop ◽  
Discrete Event ◽  
Specific Class ◽  
Production Lines ◽  
Closed Loops ◽  
Event Simulation ◽  
Automobile Assembly ◽  
Loop Network ◽  
The Impact

The aim of the work presented in this paper describes the development of a decision support system based on a discrete-event simulation model of an automobile assembly line. The model focuses at a very specific class of production lines with a four closed-loop network configuration. One key characteristic in the closed-loop system is that the number of pallets inside the first three loops has been made constant. The impact of the number of pallets circulating on the first three closed-loops and of the proportion of four-door car bodies on the performance of the production line has been thoroughly investigated. This has been translated into the number of cars produced per hour, in order to improve the availability of the entire manufacturing system.

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

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.

Use of Mathematical Models in a Mechanical Metal Industry to Improve Production Planning and Control

2021 ◽  
pp. 314-332
Author(s):  
Leoni Pentiado Godoy ◽  
Wagner Pietrobelli Bueno ◽  
Tais Pentiado Godoy ◽  
Clandia Gomes ◽  
Maria Carolina Martins Rodrigues ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Decision Making ◽  
Production Planning ◽  
Production Control ◽  
Qualitative Approach ◽  
Production Planning And Control ◽  
Planning And Control ◽  
The Cost ◽  
And Control

This chapter aims to propose an improvement in decision making in the planning sector and production control (PPC) with application of a mathematical model. In the methodology, the qualitative approach was used because the linguistic codifications are interpreted and characterized by a case study applying a questionnaire to the managers of the company of the metal mechanic sector. In this context, six constructs were structured as a proposal for performance improvement, being composed of costs, management, inspection, processes, and capacity. The chapter reports the main results achieved during fuzzy sets application, obtaining a better result compared to FAHP in which there were certain oscillations between the percentage of constructs. The construct prioritized by managers and specialists was the cost construct, reaching 38.60%, being advantageous for the industry when the cost is placed in order of manufacture (subconstruct), followed by the prioritized management construct with 28.50%.

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