Hierarchical production control for a flow shop with dynamic setup changes and random machine breakdowns

OR Spectrum ◽  
1996 ◽  
Vol 18 (2) ◽  
pp. 81-96 ◽  
Author(s):  
S. X. Bai ◽  
J. H. Burhanpurwala ◽  
M. ElHafsi ◽  
Y. -K. Tsai
Keyword(s):  
Production Control ◽  
Flow Shop ◽  
Machine Breakdowns ◽  
Hierarchical Production Control

Robust scheduling in two-stage assembly flow shop problem with random machine breakdowns: integrated meta-heuristic algorithms and simulation approach

2019 ◽  
Vol 39 (5) ◽  
pp. 944-962 ◽  
Author(s):  
Sahar Tadayonirad ◽  
Hany Seidgar ◽  
Hamed Fazlollahtabar ◽  
Rasoul Shafaei
Keyword(s):  
Manufacturing Systems ◽  
Heuristic Algorithms ◽  
Flow Shop ◽  
Imperialist Competitive Algorithm ◽  
Flow Shop Scheduling ◽  
Process Time ◽  
Two Stage ◽  
Content Type ◽  
Robust Scheduling ◽  
Machine Breakdowns

Purpose In real manufacturing systems, schedules are often disrupted with uncertainty factors such as random machine breakdown, random process time, random job arrivals or job cancellations. This paper aims to investigate robust scheduling for a two-stage assembly flow shop scheduling with random machine breakdowns and considers two objectives makespan and robustness simultaneously. Design/methodology/approach Owing to its structural and algorithmic complexity, the authors proposed imperialist competitive algorithm (ICA), genetic algorithm (GA) and hybridized with simulation techniques for handling these complexities. For better efficiency of the proposed algorithms, the authors used artificial neural network (ANN) to predict the parameters of the proposed algorithms in uncertain condition. Also Taguchi method is applied for analyzing the effect of the parameters of the problem on each other and quality of solutions. Findings Finally, experimental study and analysis of variance (ANOVA) is done to investigate the effect of different proposed measures on the performance of the obtained results. ANOVA's results indicate the job and weight of makespan factors have a significant impact on the robustness of the proposed meta-heuristics algorithms. Also, it is obvious that the most effective parameter on the robustness for GA and ICA is job. Originality/value Robustness is calculated by the expected value of the relative difference between the deterministic and actual makespan.

scholarly journals A comparison of production control systems in a flexible flow shop

2017 ◽  
Vol 13 ◽  
pp. 1090-1095 ◽  
Author(s):  
C. Silva ◽  
V. Reis ◽  
A. Morais ◽  
I. Brilenkov ◽  
J. Vaza ◽  
...  
Keyword(s):  
Control Systems ◽  
Production Control ◽  
Flow Shop ◽  
Flexible Flow Shop ◽  
Production Control Systems

A Performance-Based Dispatching Rule for Decentralised Manufacturing Planning and Production Control System

2021 ◽  
Author(s):  
Maria Grazia Marchesano ◽  
Silvestro Vespoli ◽  
Guido Guizzi ◽  
Valentina Popolo ◽  
Andrea Grassi
Keyword(s):  
Production Line ◽  
Production Control ◽  
Flow Shop ◽  
Dispatching Rule ◽  
Governance System ◽  
Manufacturing Planning ◽  
Production Control System ◽  
Short Processing Time ◽  
Machine Utilisation ◽  
First In First Out

Considering a Flow Shop production line in an Industry 4.0 setting where the Cyber-Physical System (CPS) and Internet of Things (IoTs) can be deployed, a newly Performance-based Decentralised Dispatching Rule (PDDR) is proposed. It combines known dispatching rules with the knowledge of the monitored production system state. The goal is to provide a novel dispatching rule based on production line performance oversight. The governance system considers the machine condition in terms of machine utilisation. Regarding the assessment scenario, the proposed rule has been tested and compared with the well-known Short Processing Time (SPT) and the First-In-First-Out (FIFO) rule in a higher generality way by taking into account unforeseen events that may occur in production (such as breakdowns, potential rework, micro-stops, and unplanned machine setups). The simulation results showed interesting results where the flexibility of this rule, as well as its practical use with real hypotheses are its main advantages.

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