An Optimization of Multi-product Assembly Lines Using Simulation and Multi-Objective Programming Approach

This paper investigates unreliable multi-product assembly lines with mixed (serial-parallel) layout model in which machines failures and repairing probabilities are considered. The aim of this study is to develop a multi-objective mathematical model consisting the maximization of the throughput rate of the system and the minimization of the total cost of reducing mean processing times and the total buffer capacities with respect to the optimal values of the mean processing time of each product in each workstation and the buffer capacity between workstations. For this purpose, in order to configure the structure of the mathematical model, Simulation, Design of Experiments and Response Surface Methodology are used and to solve it, the meta-heuristic algorithms including Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and Non-Dominated Ranked Genetic Algorithm (NRGA) are implemented. The validity of the multi-objective mathematical model and the application of the proposed methodology for solving the model is examined on a case study. Finally, the performance of the algorithms used in this study is evaluated. The results show that the proposed multi-objective mathematical model is valid for optimizing unreliable production lines and has the ability to achieve optimal (near optimal) solutions in other similar problems with larger scale and more complexity.IntroductionA production line consists of a sequence of workstations, in each of which parts are processed by machines. In this setup, each workstation includes a number of similar or dissimilar parallel machines, and a buffer is placed between any two consecutive workstations. In production lines, the buffer capacity and processing time of machinery have a significant impact on the system's performance. The presence of buffers helps the system to maintain production despite possible conditions or accidents, such as machinery failure or changes in processing time. Previous research has investigated production lines without any possibility of machinery failure, referred to as "safe production lines." However, in real production lines, machinery failure is inevitable. Therefore, several studies have focused on "uncertain production lines,"assuming the existence of a probability of failure in a deterministic or exponential distribution. This research examines uncertain production lines with a combined layout, resulting from the combination of parallel deployment of machines within each workstation, if necessary, and serial deployment of workstations. The objective of this research is to determine the optimal values (or values close to optimal) of the average processing time of each product in each workstation, as well as the volume of buffers, as decision variables. The approach aims to maximize the system's output while minimizing the costs associated with reducing the processing time of workstations and minimizing the total volume of buffers between stations. Moreover, simulation can be applied without interrupting the production line or consuming significant resources. In this research, due to the high cost and time involved, implementing the proposed changes on the system is not cost-effective for investigating the changes in the production system's output rate. Therefore, the simulation technique has been utilized to optimize the production line.Research methodThe present study aims to develop a multi-objective mathematical model, based on simulation, to optimize multi-product production lines. In the first step, the structure of the multi-objective mathematical model is defined, along with the basic assumptions. To adopt a realistic approach in the model structure, the simulation technique has been employed to address the first objective function, which is maximizing the output rate of the production line. To achieve this, the desired production system is simulated. The design of experiments is used to generate scenarios for implementation in the simulated model, and the response surface methodology is utilized to analyze the relationship between the input variables (such as the average processing time of each product type in each workstation and the buffer volume between stations) and the response variable (production rate).ResultsTo implement the proposed methodology based on the designed multi-objective programming model, a case study of a three-product production line with 9 workstations and 8 buffers was conducted. Subsequently, to compare the performance of the optimization algorithms, five indicators were used: distance from the ideal solution, maximum dispersion, access rate, spacing, and time. For this purpose, 30 random problems, similar to the mathematical model of the case study, were generated and solved. Based on the results obtained, both algorithms exhibited similar performance in all indices, except for the maximum dispersion index.ConclusionsIn this article, the structure of a multi-objective mathematical model was sought in uncertain multi-product production lines with the combined arrangement of machines in series-parallel (parallel installation of machines in workstations if needed and installation of workstations in series). The objective was to determine the optimal values of the average processing time of each type of product in each workstation and the buffer volume of each station, with the goals of maximizing the production rate, minimizing the costs resulting from reducing the processing time, and the total volume of inter-station buffers simultaneously. To investigate the changes in the output rate of the production system, due to the high cost and time, it was deemed not cost-effective to implement the proposed changes on the system. Therefore, the combination of simulation techniques, design of experiments, and response surface methodology was used to fit the relevant metamodel. In the proposed approach of this research, taking a realistic view of production line modeling, the probability of machinery failure, as well as the possibility of repairability and return to the system, were considered in the form of statistical distribution functions. Additionally, all time parameters, including the arrival time between the parts, the start-up time of all the machines, the processing time, the time between two failures, and the repair time of the machines, were non-deterministic and subject to statistical distributions. Finally, to solve the structured mathematical model, two meta-heuristic algorithms (NSGA-II) and (NRGA) were considered

Computer aided design for work injury elimination in production assembly systems

Work injury is one of the major obstacles in manufacturing industries especially in production assembly systems all over the world. Work injuries reduce production efficiency and threat human health. Among various types of work injuries, repetitive work injuries are the one that can be easily neglected. This thesis is about the application of computing technology to analysis and synthesis of repetitive work injuries in production assembly systems for the purpose of reduction or elimination of these injuries. A production assembly system consists of the assembly machines, products, tools, humans (workers), and particular environments. Injuries of the worker are basically caused by over stress, strain, and fatigue, which are further related to the worker’s posture. This research proposed a general methodology for constructing a software system for analysis and simulation of a worker’s postures in a virtual environment. The implementation of such a computer system was discussed. This research also proposed methods to compute work injury cost. Finally, this research proposed a more systematic method for the synthesis or re-design of worker’ postures to reduce or eliminate work injuries. The major contribution of this thesis work is to advance computing to work injury analysis and synthesis in production systems. This thesis study concludes that the computer technology is matured enough to highly automate the process of work injury analysis and synthesis. It is possible that a complete design of production systems with consideration of work injuries can be done in a much more efficient manner – perhaps reduction of the ramp-up process in the automobile industry from 6 months (typically) to one month in addition to the removal of wasted materials and potential injuries in the ramp-up process

A general computer-based methodology for work injury analysis in a production assembly line

Repetitive injuries have been a major obstacle in production assembly lines all over the world. These injuries have greatly reduced the production efficiency of assembly plants and also negatively affected human health. Various attempts have been made by the Canadian government through the Worker’s Compensation Board (WCB) to prevent the occurrences of these injuries because of the associated cost and effects. These attempts failed as the cost of injuries acquired in the workplace continues to increase. For example, in New Zealand alone, the total cost of accidents in 2005, is estimated at $300 million (Accident Compensation Corporation, 2005). In Canada, the number of accepted claims alone amount to 15623 people (Workers Compensation Board of Canada, 2003).A human body can be viewed as a mechanism that is composed of links and joints controlled by a central nervous system and are subject to stress, strain, fatigue and failure as can be observed on a regular industrial robot. But unlike the robot which is designed proactively, these stress and strain factors could be because of certain conditions such as inappropriate work posture, poor assembly line design, excessive workload, and poor work conditions. Often, it is almost uncertain to make a conceptual assessment of the appropriate ergonomic design of a production system before the assembly line is built and put in use. This research will propose a general computer-based methodology for analysis of work injuries given an assembly line where human workers perform repetitive operations. The general methodology integrates sophisticated computer software systems for biomechanics simulation with various manual measurement techniques and methods. The research further proposed a simple and handy synthesis method with which problematic areas of assembly line design, with special reference to human work design can be identified and improved. The proposed methodology for analysis and synthesis is then implemented in a real assembly line to understand the effects of different work activities on the human body. Various software packages and motion tracking techniques will be considered prior to the actual implementation of the final methodology. A rule of thumb table will also be presented as a guideline for the re-design process. The research also proposed a general procedure and specific formula within a specific regional context to calculate the costs of worker injuries in real-life assembly system. This formula thus allows us to obtain the total cost of injuries in a production assembly line, making it possible to optimize the design and operation of the assembly line

Conception et contrôle des chaînes d'approvisionnement tenant compte des phénomèmes aléatoires

Ce projet porte sur la conception et le contrôle d'un réseau manufacturier fiable tenant compte des phénomènes aléatoires. Notre objectif est de trouver et implanter les bons modes de gestion afin d'améliorer la fiabilité du réseau manufacturier qui subit différentes perturbations, ce qui permet de changer la conception initiale du réseau et donner une configuration optimale. La résolution de ce problème nécessite l'utilisation d'une approche hybride qui combine la programmation linéaire mixte en nombres entiers avec la simulation par événements discrets. Une telle approche est utilisée pour déterminer, à l'aide du modèle d'optimisation, la configuration optimale du réseau ainsi que le plan de planification, le programme linéaire sera par la suite suivi par la simulation à événements discrets pour valider, en premier lieu, les résultats mathématiques et donner, en deuxième lieu, une configuration et une planification plus réalistes et fiables en considérant les aspects aléatoires du réseau manufacturier

Systematische Analyse und Bewertung komplexer Supply Chain Prozesse bei dynamischer Festlegung des Auftragsentkopplungspunkts

Ein entscheidender Erfolgsfaktor jeder Supply Chain ist das adäquate Design ihrer Leistungserstellungsprozesse. Da diese Prozesse regelmäßig durch einen hohen Grad an Komplexität gekennzeichnet sind, stellt deren Gestaltung eine große Herausforderung dar. In dieser Forschungsarbeit wird deshalb die Frage behandelt, wie komplexe Leitungserstellungsprozesse einer Supply Chain effektiv und effizient verbessert werden können. Dazu wird eine systematische Vorgehensweise für die Analyse und Bewertung von Supply Chain Prozessen vorgestellt und im Rahmen einer Fallstudie auf eine reale Logistikkette in der Elektronikindustrie angewandt. Bei der Prozessanalyse wird eine Reduktion der Komplexität durch eine Kombination von analytischen Methoden und Simulation erzielt, sodass nicht nur die Validität der Ergebnisse, sondern auch die praktische Umsetzbarkeit gewährleistet ist. Die Bewertung von alternativen Prozessdesigns erfolgt multikriteriell und strategiebasierend, damit sowohl Zielkonflikte als auch die verfolgte Strategie der Logistikkette Berücksichtigung finden. Generell spielt die Wahl des marktbezogenen Produktionstyps (z.B. Make-to-Order, Make-to-Stock) bei der Verbesserung von Supply Chain Prozessen eine entscheidende Rolle. Daher wird auf diesen Aspekt besonders eingegangen, wobei der hybride Produktionstyp Make-to-Forecast in einem Supply Chain-Kontext in der Fallstudie implementiert wird