Production Planning Models using Max-Plus Algebra

2013 ◽  
pp. 227-257 ◽  
Author(s):  
Arun N. Nambiar ◽  
Aleksey Imaev ◽  
Robert P. Judd ◽  
Hector J. Carlo
Keyword(s):  
Manufacturing Systems ◽  
Stochastic Systems ◽  
Performance Metrics ◽  
Job Shop ◽  
Flow Shop ◽  
Linear Equations ◽  
Building Blocks ◽  
Buffer Allocation ◽  
Planning Models ◽  
Machining Operations

The chapter presents a novel building block approach to developing models of manufacturing systems. The approach is based on max-plus algebra. Within this algebra, manufacturing schedules are modeled as a set of coupled linear equations. These equations are solved to find performance metrics such as the make span. The chapter develops a generic modeling block with three inputs and three outputs. It is shown that this structure can model any manufacturing system. It is also shown that the structure is hierarchical, that is, a set of blocks can be reduced to a single block with the same three inputs and three output structure. Basic building blocks, like machining operations, assembly, and buffering are derived. Job shop, flow shop, and cellular system applications are given. Extensions of the theory to buffer allocation and stochastic systems are also outlined. Finally, several numerical examples are given throughout the development of the theory.

And The World Came To See: New Manufacturing System Designs and Industrial Revolutions

2002 ◽  
Author(s):  
J. T. Black ◽  
David S. Cochran
Keyword(s):  
System Design ◽  
Systems Engineering ◽  
Lean Manufacturing ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Job Shop ◽  
Flow Shop ◽  
The World ◽  
Industrial Revolutions ◽  
New System

AND THE WORLD CAME TO SEE. When a new manufacturing system design (MSD) is developed by a company or a group of companies, the rest of the world comes to those factories to learn about the new system. In the last 200 years, three new factory designs have evolved, called the job shop, the flow shop and the lean shop. Each is based on a new system design — a functional design, a product flow design and a linked cell design. New factory designs lead to new industrial leaders and even new industrial revolutions (IR’s). Two appendixes are included: One outlines the implementation strategy for the lean shop and the other is a discussion of lean manufacturing from the viewpoint of K. Hitomi, Japanese professor of manufacturing systems engineering.

scholarly journals Novel Complexity Indicator of Manufacturing Process Chains and Its Relations to Indirect Complexity Indicators

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Vladimir Modrak ◽  
Zuzana Soltysova
Keyword(s):  
Manufacturing Process ◽  
Material Flow ◽  
Manufacturing Systems ◽  
Job Shop ◽  
Flow Shop ◽  
Manufacturing Processes ◽  
Process Chains

Manufacturing systems can be considered as a network of machines/workstations, where parts are produced in flow shop or job shop environment, respectively. Such network of machines/workstations can be depicted as a graph, with machines as nodes and material flow between the nodes as links. The aim of this paper is to use sequences of operations and machine network to measure static complexity of manufacturing processes. In this order existing approaches to measure the static complexity of manufacturing systems are analyzed and subsequently compared. For this purpose, analyzed competitive complexity indicators were tested on two different manufacturing layout examples. A subsequent analysis showed relevant potential of the proposed method.

Maintenance on Job Shop Industry: Review and Analysis

2016 ◽  
Vol 842 ◽  
pp. 365-372 ◽  
Author(s):  
Herman Budi Harja ◽  
Tri Prakosa ◽  
Yatna Yuwana Martawirya
Keyword(s):  
Manufacturing Systems ◽  
Job Shop ◽  
Flow Shop ◽  
Dynamic Condition ◽  
Maintenance Optimization ◽  
Reliability Growth ◽  
Monitoring Cost ◽  
Reliability Modeling ◽  
Maintenance Schedule ◽  
Reliability Improvement

This paper presents overviews about reliability and maintainability of equipment especially for job-shop manufacturing systems. The job shop industry has the characteristics of a more dynamic production than flow shop industries, where products with a variety of great but small amounts. Its dynamic condition certainly contributes directly to the failure rate and reliability growth of equipment. Therefore, proper maintenance should be done as the reliability improvement. Stages of reliability improvement are reliability modeling, reliability analysis and maintenance optimization. This stage is based on reliability growth of equipment that is indicated the deterioration process of failure components, it can be build from maintenance data history or condition data monitoring.. Cost is often considered in points of a maintenance schedule. This cost was affected by minimizing the negative effects of maintenance and maximizing the benefit of production. The attention at reliability and maintenance optimization is a well researches area until now. This paper presents a brief review of existing reliability and maintenance research. Several reliable methods in this area are discussed and maintenance on job-shop industry as future prospects is investigated. It is shown in this paper that some aspect in the area of maintenance on job-shop industry steel needs to be deeply developed.

DYNAMIC SCHEDULING OF MANUFACTURING SYSTEMS WITH MACHINE LEARNING

2001 ◽  
Vol 12 (06) ◽  
pp. 751-762 ◽  
Author(s):  
PAOLO PRIORE ◽  
DAVID DE LA FUENTE ◽  
ALBERTO GOMEZ ◽  
JAVIER PUENTE
Keyword(s):  
Machine Learning ◽  
Manufacturing Systems ◽  
Job Shop ◽  
Dynamic Scheduling ◽  
Flow Shop ◽  
Dispatching Rules ◽  
Heuristic Rules ◽  
Learning Program ◽  
Training Examples ◽  
Definition Of

A common way of scheduling jobs dynamically in a manufacturing system is by means of dispatching rules. The drawback of this method is that the performance of these rules depends on the state the system is in at each moment, and no one rule exists that overrules the rest in all the possible states that the system may be in. It would therefore be interesting to use the most appropriate rule at each moment. To achieve this goal, a scheduling approach which uses machine learning is presented in this paper. The methodology proposed in this paper may be divided into five basic steps. Firstly, definition of the appropriate control attributes for identifying the relevant manufacturing patterns. In second place, creation of a set of training examples using different values of the control attributes. Subsequently, acquiring of heuristic rules by means of a machine learning program. Then, using of the previously calculated heuristic rules to select the most appropriate dispatching rules, and finally testing of the performance of the approach. The approach that we propose is applied to a flow shop system and to a classic job shop configuration. The results demonstrate that this approach produces an improvement in the performance of the system when compared to the traditional method of using dispatching rules.

Multi-objective optimization of job shops with automated guided vehicles: A non-dominated sorting cuckoo search algorithm

2020 ◽  
pp. 1748006X2094653
Author(s):  
Behzad Karimi ◽  
Seyed Taghi Akhavan Niaki ◽  
Amir Hossein Niknamfar ◽  
Mahsa Gareh Hassanlu
Keyword(s):  
Manufacturing Systems ◽  
Production Efficiency ◽  
Performance Metrics ◽  
Job Shop ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Automated Guided Vehicles ◽  
Job Shops ◽  
Multi Objective

The reliability of machinery and automated guided vehicle has been one of the most important challenges to enhance production efficiency in several manufacturing systems. Reliability improvement would result in a simultaneous reduction of both production times and transportation costs of the materials, especially in automated guided vehicles. This article aims to conduct a practical multi-objective reliability optimization model for both automated guided vehicles and the machinery involved in a job-shop manufacturing system, where different machines and the storage area through some parallel automated guided vehicles handle materials, parts, and other production needs. While similar machines in each shop are limited to failures based on either an Exponential or a Weibull distribution via a constant rate, the machines in different shops fail based on different failure rates. Meanwhile, as the model does not contain any closed-form equation to measure the machine reliability in the case of Weibull failure, a simulation approach is employed to estimate the shop reliability to be further maximized using the proposed model. Besides, the automated guided vehicles are restricted to failures according to an Exponential distribution. Furthermore, choosing the best locations of the shops is proposed among some potential places. The proposed NP-Hard problem is then solved by designing a novel non-dominated sorting cuckoo search algorithm. Furthermore, a multi-objective teaching-learning-based optimization, as well as a multi-objective invasive weed optimization are designed to validate the results obtained. Ultimately, a novel AHP-TOPSIS method is carried out to rank the algorithms in terms of six performance metrics.

Resource Allocation and Job Dispatching for Unreliable Flexible Flow Shop Manufacturing System

2012 ◽  
Vol 445 ◽  
pp. 947-952
Author(s):  
Umar M. Al-Turki ◽  
Haitham Saleh ◽  
Tamer Deyab ◽  
Yasser Almoghathawi
Keyword(s):  
Resource Allocation ◽  
Production Scheduling ◽  
Manufacturing Systems ◽  
Production Efficiency ◽  
Stochastic Systems ◽  
Flow Shop ◽  
Discrete Event ◽  
Batch Size ◽  
Objective Functions ◽  
Flexible Flow Shop

Resource allocation, product batching and production scheduling are three different problems in manufacturing systems of different structures such as flexible flow shop manufacturing systems. These problems are usually dealt with independently for a certain objective function related to production efficiency and effectiveness. Handling all of them in an integrated manner is a challenge facing many manufacturing systems in practice and that challenge increases for highly complicated and stochastic systems. Random arrival of products, machine setup time requirements, unexpected machine breakdowns, and multiple conflicting objective functions are some of the common complications in such systems. This research attempts to study the integrated problem under the mentioned complications with various objective functions. The decisions parameters are the batch size, the number of machines at each workstation, and the dispatching policy. Discrete event simulation is used as an optimization tools. The system is modeled using the ARENA software and different scenarios are tested for optimum parameter selection under different conditions.

scholarly journals A Literature Review of Energy Efficiency and Sustainability in Manufacturing Systems

2021 ◽  
Vol 11 (16) ◽  
pp. 7366
Author(s):  
Paolo Renna ◽  
Sergio Materi
Keyword(s):  
Energy Efficiency ◽  
Renewable Energy ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Job Shop ◽  
Flow Shop ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Future Directions ◽  
Change Mitigation

Climate change mitigation, the goal of reducing CO2 emissions, more stringent regulations and the increment in energy costs have pushed researchers to study energy efficiency and renewable energy sources. Manufacturing systems are large energy consumers and are thus responsible for huge greenhouse gas emissions; for these reasons, many studies have focused on this topic recently. This review aims to summarize the most important papers on energy efficiency and renewable energy sources in manufacturing systems published in the last fifteen years. The works are grouped together, considering the system typology, i.e., manufacturing system subclasses (single machine, flow shop, job shop, etc.) or the assembly line, the developed energy-saving policies and the implementation of the renewable energy sources in the studied contexts. A description of the main approaches used in the analyzed papers was discussed. The conclusion reports the main findings of the review and suggests future directions for the researchers in the integration of renewable energy in the manufacturing systems consumption models.

A Two-Stage Hybrid Algorithm for Flexible Job-Shop Scheduling

2011 ◽  
Vol 268-270 ◽  
pp. 476-481
Author(s):  
Li Gao ◽  
Ke Lin Xu ◽  
Wei Zhu ◽  
Na Na Yang
Keyword(s):  
Genetic Algorithm ◽  
Hybrid Algorithm ◽  
Job Shop ◽  
Flow Shop ◽  
Job Shop Scheduling ◽  
Selection Procedure ◽  
Dynamic Programming Method ◽  
Two Stage ◽  
Simulated Annealing Genetic Algorithm ◽  
Mutation Operators

A mathematical model was constructed with two objectives. A two-stage hybrid algorithm was developed for solving this problem. At first, the man-hour optimization based on genetic algorithm and dynamic programming method, the model decomposes the flow shop into two layers: sub-layer and patrilineal layer. On the basis of the man-hour optimization，A simulated annealing genetic algorithm was proposed to optimize the sequence of operations. A new selection procedure was proposed and hybrid crossover operators and mutation operators were adopted. A benchmark problem solving result indicates that the proposed algorithm is effective.

An experimental study on feature-based SLAM for multi-legged robots with RGB-D sensors

2017 ◽  
Vol 44 (4) ◽  
pp. 428-441 ◽  
Author(s):  
Michał R. Nowicki ◽  
Dominik Belter ◽  
Aleksander Kostusiak ◽  
Petr Cížek ◽  
Jan Faigl ◽  
...  
Keyword(s):  
Performance Metrics ◽  
State Of The Art ◽  
Building Blocks ◽  
Bundle Adjustment ◽  
The State ◽  
Legged Robots ◽  
Evaluation Methodology ◽  
Walking Robots ◽  
Content Type ◽  
Feature Based

Purpose This paper aims to evaluate four different simultaneous localization and mapping (SLAM) systems in the context of localization of multi-legged walking robots equipped with compact RGB-D sensors. This paper identifies problems related to in-motion data acquisition in a legged robot and evaluates the particular building blocks and concepts applied in contemporary SLAM systems against these problems. The SLAM systems are evaluated on two independent experimental set-ups, applying a well-established methodology and performance metrics. Design/methodology/approach Four feature-based SLAM architectures are evaluated with respect to their suitability for localization of multi-legged walking robots. The evaluation methodology is based on the computation of the absolute trajectory error (ATE) and relative pose error (RPE), which are performance metrics well-established in the robotics community. Four sequences of RGB-D frames acquired in two independent experiments using two different six-legged walking robots are used in the evaluation process. Findings The experiments revealed that the predominant problem characteristics of the legged robots as platforms for SLAM are the abrupt and unpredictable sensor motions, as well as oscillations and vibrations, which corrupt the images captured in-motion. The tested adaptive gait allowed the evaluated SLAM systems to reconstruct proper trajectories. The bundle adjustment-based SLAM systems produced best results, thanks to the use of a map, which enables to establish a large number of constraints for the estimated trajectory. Research limitations/implications The evaluation was performed using indoor mockups of terrain. Experiments in more natural and challenging environments are envisioned as part of future research. Practical implications The lack of accurate self-localization methods is considered as one of the most important limitations of walking robots. Thus, the evaluation of the state-of-the-art SLAM methods on legged platforms may be useful for all researchers working on walking robots’ autonomy and their use in various applications, such as search, security, agriculture and mining. Originality/value The main contribution lies in the integration of the state-of-the-art SLAM methods on walking robots and their thorough experimental evaluation using a well-established methodology. Moreover, a SLAM system designed especially for RGB-D sensors and real-world applications is presented in details.

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