Assembly System Reconfiguration Planning

2013 ◽  
Vol 135 (4) ◽  
Author(s):  
April Bryan ◽  
S. Jack Hu ◽  
Yoram Koren
Keyword(s):  
Genetic Algorithm ◽  
Life Cycle ◽  
Life Cycle Cost ◽  
Product Family ◽  
Life Cycles ◽  
Dynamic Program ◽  
Assembly System ◽  
Assembly Systems ◽  
System Reconfiguration ◽  
Reconfiguration Planning

Decreasing product life cycles and reduced product development times have led to a need for new strategies for coping with the rapid rate of product family design changes. In this paper, assembly system reconfiguration planning (ASRP) is introduced as a method for cost effectively designing several generations of assembly systems in order to produce a product family that gradually evolves over time. In the ASRP approach, the possible assembly systems for each generation are first considered and then the sequence of assembly system configurations that minimize the life cycle cost of the process are selected. A nonlinear integer optimization formulation is developed for finding the cost minimizing assembly system reconfiguration plan using the ASRP approach. Dynamic programming and genetic algorithm are used to solve the optimization problem. Simulation results indicate that the ASRP approach leads to the minimum life cycle costs of the assembly system, and the relative cost of reconfiguration and production have an impact on the assembly system reconfiguration plan selected. Comparison of the results of the dynamic program and genetic algorithm indicate that the dynamic program is more computationally efficient for small problems and genetic algorithm is preferred for larger problems.

Methodology for Solving the Assembly System Reconfiguration Planning Problem

2011 ◽  
Author(s):  
A. Bryan ◽  
S. J. Hu ◽  
Y. Koren
Keyword(s):  
Product Family ◽  
Assembly System ◽  
Assembly Systems ◽  
Planning Problem ◽  
Systems Methodology ◽  
Product Families ◽  
System Reconfiguration ◽  
Reconfiguration Planning ◽  
Successive Generations ◽  
The Cost

The need to cost effectively introduce new generations of product families within ever decreasing time frames have led manufacturers to seek product development strategies with a multigenerational outlook. Co-evolution of product families and assembly systems is a methodology that leads to the simultaneous design of several generations of product families and reconfigurable assembly systems that optimize life cycle costs. Two strategies that are necessary for the implementation of the co-evolution of product families and assembly systems methodology are: (1) The concurrent design of product families and assembly systems and (2) Assembly system reconfiguration planning (ASRP). ASRP is used for the determination of the assembly system reconfiguration plans that minimize the cost of producing several generations of product families. More specifically, the objective of ASRP is to minimize the net present cost of producing successive generations of products. This paper introduces a method for finding optimum solutions to the ASRP problem. The solution methodology involves the generation of a staged network of assembly system plans for all the generations that the product family is expected to be produced. Each stage in the network represents a generation that the product family is produced, while each state within a stage represents a potential assembly system configuration. A novel algorithm for generating the states (i.e. assembly system configurations) within each generation is also introduced. A dynamic program is used to find the cost minimizing path through the network. An example is used to demonstrate the implementation of the ASRP methodology.

Assembly System Reconfiguration Planning Using Genetic Algorithm

2008 ◽  
Author(s):  
A. Bryan ◽  
S. J. Hu ◽  
Y. Koren
Keyword(s):  
Genetic Algorithm ◽  
Manufacturing Systems ◽  
Cost Effective ◽  
New Product ◽  
Assembly System ◽  
Assembly Systems ◽  
Reconfigurable Manufacturing ◽  
Product Families ◽  
System Reconfiguration ◽  
Reconfiguration Planning

Due to increased competition, the rate at which manufacturers introduce new product families to the market is increasing. However, the cost of changing manufacturing facilities to produce new product families can outweigh the benefits obtained from increased revenue. Reconfigurable Manufacturing Systems (RMSs) have been proposed as a cost effective strategy for manufacturing product families. Although methods for measuring RMS scalability and convertibility exist, there is a lack of methods for obtaining reconfiguration plans for assembly systems. This paper introduces assembly system reconfiguration planning (ASRP) as method to obtain reconfiguration plans for assembly systems. A genetic algorithm is developed for solving the ASRP problem.

Reliability Analysis of Repairable Systems Subject to System Modifications

1998 ◽  
Author(s):  
Z. H. Jiang ◽  
L. H. Shu ◽  
B. Benhabib
Keyword(s):  
Life Cycle ◽  
Steady State ◽  
Cost Estimation ◽  
Life Cycle Cost ◽  
Repairable Systems ◽  
Environmentally Conscious ◽  
Reliability Indices ◽  
Reliability Models ◽  
System Reconfiguration ◽  
Environmentally Conscious Design

Abstract This paper approaches environmentally conscious design by further developing a reliability model that facilitates design for reuse. Many reliability models are not suitable for describing systems that undergo repairs performed during remanufacture and maintenance because the models do not allow the possibility of system reconfiguration. In this paper, expressions of reliability indices of a model that allows system reconfiguration are developed to enable life-cycle cost estimation for repairable systems. These reliability indices of a population of repairable systems are proven theoretically to reach steady state. The expressions of these indices at steady state are obtained to gain insight into the model behavior, and to facilitate life-cycle cost estimation.

Research on the Multi-Objective Optimization Model of System-Level BIT Testability Index Determination

2011 ◽  
Vol 121-126 ◽  
pp. 2223-2227 ◽  
Author(s):  
Chun Sheng Zhu ◽  
Qi Zhang ◽  
Fan Tun Su ◽  
Hong Liang Ran
Keyword(s):  
Genetic Algorithm ◽  
Life Cycle ◽  
Mathematical Models ◽  
Optimization Model ◽  
System Reliability ◽  
Life Cycle Cost ◽  
System Level ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Life Circle

By weighing reliability, maintainability, availability and life-cycle cost of equipment which are influenced by testability，the testability indexes of system level BIT are determined on the basis of maximum system reliability & maintainability and minimum the life-circle cost. The influence mathematical models of system reliability, maintainability, availability and life-circle cost are established. According to these mathematical models, the multi-objective optimization model of system-level BIT testability indexes is established. The multi-objective optimization model is solved using Non-dominated Sorting Genetic Algorithm II, and the validity of the multi-objective optimization model is proved through an example.

A Decision Support Framework for Cost-Effective and Energy-Efficient Shipping

2020 ◽  
Author(s):  
Khanh Q. Bui ◽  
Lokukaluge P. Perera
Keyword(s):  
Life Cycle ◽  
Decision Support ◽  
Energy Efficient ◽  
Life Cycle Cost ◽  
Performance Monitoring ◽  
Cost Effective ◽  
Life Cycles ◽  
Maritime Industry ◽  
Decision Support Framework ◽  
Maritime Operations

Abstract Stringent regulations regarding environmental protection and energy efficiency (i.e., emission limits regarding NOx, SOx pollutants and the IMO greenhouse gases reduction target) will mark a significant shift to the maritime industry. In the first place, the shipping industry has strived to work towards feasible technologies for regulatory compliance. Nevertheless, life cycle cost appraisal attaches much consideration of decision-makers when it comes to investment decisions on new technologies. Therefore, the life cycle cost analysis (LCCA) is proposed in this study to evaluate the cash flow budgeting and cost performance of the proposed technologies over their life cycles. In the second place, environmental regulations may support innovation especially in the era of digitalization. The industrial digitalization is expected to revolutionize all of the aspects of shipping and enable the achievement of energy-efficient and environmental-friendly maritime operations. The so-called Internet of things (IoT) with the utilization of sensor technologies as well as data acquisition systems can facilitate the respective maritime operations by means of vessel operational performance monitoring. The big data sets obtained from IoT should be properly analyzed with the help of Artificial Intelligence (AI) and Machine Learning (ML) approaches. Our contribution in this paper is to propose a decision support framework, which comprises the LCCA analysis and advanced data analytics for ship performance monitoring, will play a pivotal role for decision-making processes towards cost-effective and energy-efficient shipping.

scholarly journals Considering Product Life Cycle Cost Purchasing Strategy for Solving Vendor Selection Problems

2019 ◽  
Vol 11 (13) ◽  
pp. 3739
Author(s):  
Chien-Wen Shen ◽  
Yen-Ting Peng ◽  
Chang-Shu Tu
Keyword(s):  
Life Cycle ◽  
Life Cycle Cost ◽  
Product Life Cycle ◽  
Economies Of Scale ◽  
Rejection Rate ◽  
Life Cycles ◽  
High Tech ◽  
Vendor Selection ◽  
Product Life ◽  
Strategic Relationships

The framework of product life cycle (PLC) cost analysis is one of the most important evaluation tools for a contemporary high-tech company in an increasingly competitive market environment. The PLC-purchasing strategy provides the framework for a procurement plan and examines the sourcing strategy of a firm. The marketing literature emphasizes that ongoing technological change and shortened life cycles are important elements in commercial organizations. From a strategic viewpoint, the vendor has an important position between supplier, buyer and manufacturer. The buyer seeks to procure the products from a set of vendors to take advantage of economies of scale and to exploit opportunities for strategic relationships. However, previous studies have seldom considered vendor selection (VS) based on PLC cost (VSPLCC) analysis. The purpose of this paper is to solve the VSPLCC problems considering the situation of a single buyer–multiple supplier. For this issue, a new VSPLCC procurement model and solution procedure are derived in this paper to minimize net cost, rejection rate, late delivery and PLC cost subject to vendor capacities and budget constraints. Moreover, a real case in Taiwan is provided to show how to solve the VSPLCC procurement problem.

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