scholarly journals Analysis of the Robustness of Production Scheduling in Aeronautical Manufacturing Using Simulation: A Case Study

2017 ◽  
pp. 174-183 ◽  
Author(s):  
R. Pulido ◽  
T. Borreguero-Sanchidrián ◽  
A. García-Sánchez ◽  
M. Ortega-Mier
Keyword(s):  
Production Scheduling

Decision Support Tools for Managing Unpredictability in the Supply Chain

2000 ◽  
Author(s):  
Carol Vesier
Keyword(s):  
Supply Chain ◽  
Decision Support ◽  
Inventory Management ◽  
Production Scheduling ◽  
Capital Investment ◽  
Investment Strategy ◽  
Decision Support Tools ◽  
Business Outcomes ◽  
Support Tools

Abstract Effectively managing unpredictability requires decision support tools that can predict the financial and business outcomes of various supply chain strategies. This paper will discuss the role of these decision support tools and their characteristics as well as review a case study. In the case study, decision support tools facilitated development of strategies that increased after tax profit by $140 Million. These strategies included: • Reliability improvement strategy: Identifying the reliability improvements that offered the biggest profitability impact. • Supply chain strategy: Defining inventory management and production scheduling rules that ensured order shipment within two days. • Capital investment strategy: Defining when new capacity should come on line as well as the minimum capital investment.

Simulated Annealing for Production Scheduling: A Case Study

2015 ◽  
pp. 107-114
Author(s):  
António Santos Marques ◽  
Nelson Chibeles-Martins ◽  
Tânia Pinto-Varela
Keyword(s):  
Simulated Annealing ◽  
Production Scheduling

scholarly journals How environment dynamics affects production scheduling: Requirements for development of CPPS models

2021 ◽  
Vol 49 (4) ◽  
pp. 827-834
Author(s):  
Cátia Alves ◽  
Goran Putnik ◽  
Leonilde Varela
Keyword(s):  
Production Scheduling ◽  
Manufacturing Systems ◽  
New Technologies ◽  
Production Systems ◽  
Strong Positive Correlation ◽  
Systems Architecture ◽  
Study Results ◽  
Cyber Physical Production Systems ◽  
Scheduling Models

Production scheduling can be affected by many disturbances in the manufacturing system, and consequently, the feasible schedules previously defined became obsolete. Emerging of new technologies associated with Industry 4.0, such as Cyber-Physical Production Systems, as a paradigm of implementation of control and support in decision making, should embed the capacity to simulate different environment scenarios based on the data collected by the manufacturing systems. This paper presents the evaluation of environment dynamics effect on production scheduling, considering three scheduling models and three environment scenarios, through a case study. Results show that environment dynamics affect production schedules, and a very strong or strong positive correlation between environment dynamics scenarios and total completion time with delay, over three scheduling paradigms. Based on these results, the requirement for mandatory inclusion of a module for different environment dynamics scenarios generation and the corresponded simulations, of a Cyber-Physical Production Systems architecture, is confirmed.

Sign in / Sign up

Export Citation Format

Share Document