Solving Many-Objective Car Sequencing Problems on Two-Sided Assembly Lines Using an Adaptive Differential Evolutionary Algorithm

The car sequencing problem (CSP) is addressed in this paper. The original environment of the CSP is modified to reflect real practices in the automotive industry by replacing the use of single-sided straight assembly lines with two-sided assembly lines. As a result, the problem becomes more complex caused by many additional constraints to be considered. Six objectives (i.e. many objectives) are optimised simultaneously including minimising the number of colour changes, minimising utility work, minimising total idle time, minimising the total number of ratio constraint violations and minimising total production rate variation. The algorithm namely adaptive multi-objective evolutionary algorithm based on decomposition hybridised with differential evolution algorithm (AMOEA/D-DE) is developed to tackle this problem. The performances in Pareto sense of AMOEA/D-DE are compared with COIN-E, MODE, MODE/D and MOEA/D. The results indicate that AMOEA/D-DE outperforms the others in terms of convergence-related metrics

A survey of scheduling problems with setup times or costs

Author name used in this publication: C. T. NgAuthor name used in this publication: T. C. E. Cheng2007-2008 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Integrated Optimization of Production Planning and Scheduling in Mixed Model Assembly Line

AbstractIn order to solve the separation in the traditional serial production planning and scheduling in mixed model assembly line, the integrated optimization complete model of production planning and scheduling based on multiple objectives and constraints was constructed. Since the integrated optimization complete model is difficult to solve, the heuristic approach was adopt, and the modified discrete particle swarm optimization(MDPSO) was presented to solve the model. The experiments verifies the presented model and algorithm can realize the simultaneously optimization of production planning and scheduling in mixed model assembly line and contribute to performance improvement and the application scope expand of the new intelligent optimization

Modeling and Performance Analysis of Manufacturing Systems Using Max-Plus Algebra

In response to increased competition, manufacturing systems are becoming more complex in order to provide the flexibility and responsiveness required by the market. The increased complexity requires decision support tools that can provide insight into the effect of system changes on performance in an efficient and timely manner. Max-Plus algebra is a mathematical tool that can model manufacturing systems in linear equations similar to state-space equations used to model physical systems. These equations can be used in providing insight into the performance of systems that would otherwise require numerous time consuming simulations. This research tackles two challenges that currently hinder the applicability of the use of max-plus algebra in industry. The first problem is the difficulty of deriving the max-plus equations that model complex manufacturing systems. That challenge was overcome through developing a method for automatically generating the max-plus equations for manufacturing systems and presenting them in a form that allows analyzing and comparing any number of possible line configurations in an efficient manner; as well as giving insights into the effects of changing system parameters such as the effects of adding buffers to the system or changing buffers sizes on various system performance measures. The developed equations can also be used in the operation phase to analyze possible line improvements and line reconfigurations due to product changes. The second challenge is the absence of max-plus models for special types of manufacturing systems. For this, max-plus models were developed for the first time for modeling mixed model assembly lines (MMALs) and re-entrant manufacturing systems. The developed methods and tools are applied to case studies of actual manufacturing systems to demonstrate the effectiveness of the developed tools in providing important insight and analysis of manufacturing systems performance. While not covering all types of manufacturing systems, the models presented in this thesis represent a wide variety of systems that are structurally different and thus prove that max-plus algebra is a practical tool that can be used by engineers and managers in modeling and decision support both in the design and operation phases of manufacturing systems

Assignment of Customer-Specific Orders to Plants with Mixed-Model Assembly Lines in Global Production Networks

Build-to-order series production is gaining increasing importance as markets demand customer-specific product variants. Orders have to be assigned to plants and periods in global production networks and then to lines and cycles. Consequently, respective workloads as well as supplied materials have to be balanced due to limitations in resource capacities. As first step planning defines the solution space for second step planning, this paper introduces a mathematical model for order assignments to plants and periods anticipating assignments to lines and cycles. Given that orders are not fully specified for first step planning, the approach includes provisions for dealing with uncertainty

Use of Excel worksheets with user-friendly interface in batch process (PSBP) to minimize the makespan

In the chemical industry, the necessity for scheduling is becoming more pronounced, especially in batch production mode. Nowadays, planning industrial activities is a necessity for survival. Intense competition requires diversified products and delivery in accordance with the requirements of consumers. These activities require quick decision making and the lowest possible cost, through an efficient Production Scheduling. So, this work addresses the Permutation Flow Shop scheduling problem, characterized as Production Scheduling in Batch Process (PSBP), with the objective of minimizing the total time to complete the schedule (Makespan). A method to approach the problem of production scheduling is to turn it into Mixed Integer Linear Programming- MILP, and to solve it using commercial mathematical programming packages. In this study an electronic spreadsheet with user-friendly interface (ESUFI) was developed in Microsoft Excel. The ease of manipulation of the ESUFI is quite evident, as with the use of VBA language a user-friendly interface could be created between the user and the spreadsheet itself. The results showed that it is possible to use the ESUFI for small problems

Bottleneck Management through Strategic Sequencing in Smart Manufacturing Systems

Nowadays, industries put a significant emphasis on finding the optimum order for carrying out jobs in sequence. This is a crucial element in determining net productivity. Depending on the demand criterion, all production systems, including flexible manufacturing systems, follow a predefined sequence of job-based machine operations. The complexity of the problem increases with increasing machines and jobs to sequence, demanding the use of an appropriate sequencing technique. The major contribution of this work is to modify an existing algorithm with a very unusual machine setup and find the optimal sequence which will really minimize the makespan. This custom machine setup completes all tasks by maintaining precedence and satisfying all other constraints. This thesis concentrates on identifying the most effective technique of sequencing which will be validated in a lab environment and a simulated environment. It illustrates some of the key methods of addressing a circular non permutation flow shop sequencing problem with some additional constraints. Additionally, comparisons among the various heuristics algorithms are presented based on different sequencing criteria. The optimum sequence is provided as an input to a real-life machine set up and a simulated environment for selecting the best performing algorithm which is the basic goal of this research. To achieve this goal, at first, a code using python programming language was generated to find an optimum sequence. By analyzing the results, the makespan is increasing with the number of jobs but additional pallet constraint shows, adding more pallets will help to reduce makespan for both flow shops and job shops. Though the sequence obtained from both algorithms is different, for flow shops the makespan remains same for both cases but in the job shop scenario Nawaz, Enscore and Ham (NEH) algorithms always perform better than Campbell Dudek Smith (CDS) algorithms. For job shops with different combinations the makespan decreases mostly for maximum percentage of easy category jobs combined with equal percentage of medium and complex category jobs

Abandoned project restoration model (APRM) for residential construction projects

Incompletion of construction projects is a common phenomenon in Malaysia. Project abandonment has given an adverse consequences to the economy, society and environment. In the best interest of the end users and other parties involved in the contract, the best resolution for this abandoned projects is to successfully revive them, which has its’ stages and barriers along the way as well. The main aim of this research is to develop an effective model as a guide towards project restoration which could be used to mitigate the issue of abandoned residential construction projects in Malaysia. Identifying the factors contributing towards the restoration of the abandoned projects are important to have a successful completed project. This research was conducted in the purpose of identifying those significant factors in order to obtain the restoration process for abandoned projects where lastly the Abandoned Project Restoration Model (APRM) was developed. The research focuses on residential construction projects. This research comprises of both quantitative and qualitative approaches and process, where a pilot survey and full survey, and as well as interview analysis were conducted. Factor model was developed using AMOS and lastly the developed model was validated and tested by related officials. The outcome of this research showed that the most significant factor for abandoned project restoration is Management Aspects. A complete restoration process based on the significant factors identified were also obtained. This model is seen as useful in contributing and as well as assisting the restoration of the abandoned projects in Malaysia and could be used as a guideline for that purpose

Optimal sequencing and lot sizing in a multi-model synchronous assembly line

This work presents a mixed-integer nonlinear mathematical pro-gramming (MINLP) model aiming at optimizing the sum of transition and in-ventory carrying costs in a multi-model synchronous assembly line. Different products are assembled in the same line in runs or campaigns, whose sequence and length should be optimally determined. As products show different cycle times, transition periods are of particular interest due to the productivity reduc-tion. The proposed model precisely accounts for transient periods, at the time it incorporates further details such as semi-elaborate stocks. It is successfully ap-plied to a real-world case study of the argentine truck trailer industry.Sociedad Argentina de Informática e Investigación Operativa (SADIO