Ali Siadat

Improved algorithm for tolerance allocation based on Monte Carlo simulation and discrete optimization

The allocation of design and manufacturing tolerances has a significant effect on both manufacturing cost and quality. This paper considers nonlinearly constrained tolerance allocation problems. The purpose is to minimize the ratio between the sum of the manufacturing costs (tolerances costs) and the risk (probability of the respect of geometrical requirements). The techniques of Monte Carlo simulation and genetic algorithm are adopted to solve these problems. As the simplest and the popular method for non-linear statistical tolerance analysis, the Monte Carlo simulation is introduced into the frame. Moreover, in order to make the frame efficient, the genetic algorithm is improved according to the features of the Monte Carlo simulation. An illustrative example (hyperstatic mechanism) is given to demonstrate the efficiency of the proposed approach.

A New Method for Location Selection: A Hybrid Analysis

Site selection is a part of strategic management activities. Location selection decisions involved many factors that may be conflicting in nature. Considering the tangible along with intangible factors in location selection problem, this paper propose a hybrid method of multi criteria decision making (MCDM) that make it possible to select the optimal location that satisfies the decision maker. With the aid of fuzzy AHP, our proposed model considers objective, critical, and subjective factors as the three main common factors in location analysis. The last two factors, critical and subjective factors, are defined by decision makers judgments for more adoption with the real world problems. Besides, analysis of a numerical example and the sensitivity analysis are discussed to clarify the practicability and effectiveness of the proposed model in the facility location problem.

A cell formation problem considering machine utilization and alternative process routes by scatter search

Cell formation (CF) is the first step in the design of cellular manufacturing systems (CMSs), which has been recognized as an effective way to enhance the productivity in a factory. There is a set of criteria on which to judge route of product, machine grouping and part family simultaneously in terms of the effective utilization of these cells. In this study, we consider four objectives simultaneously: (1) Minimizing the total fixed and variable cost including costs of purchasing, operation, and maintenance; (2) minimizing cost of intercellular movements; (3) maximizing the utilization of machines in the system; and (4) minimizing deviations among the levels of the cell utilization (i.e., balancing the workload between cells). In this paper, these objectives are first weighted by their relative importance and then a new mathematical model is presented. To solve this model, a scatter search (SS) algorithm is proposed to select a process plan for each part with the minimum cost along with forming the part family and machine grouping simultaneously. The performance of the proposed SS is compared with the Lingo 8.0 software. A number of test problems are carried out to verify the good ability of the proposed SS in terms of the solution quality and computational time. The computational results reveal that the SS finds promising results, especially in the case of large-sized problems.

An intuitionistic fuzzy grey model for selection problems with an application to the inspection planning in manufacturing firms

Abstract Most of complex selection problems in real-life applications are considered under multiple conflicting attributes for manufacturing firms. The appropriate selection plays an important role in the firm׳s performance from the tactical and operational viewpoints. The classical methods for the selection problems in manufacturing firms are inadequate to deal with uncertainties, including insufficiency in information availability and the imprecise or vague nature in experts׳ judgments and preferences. To overcome these difficulties, this paper introduces a novel distance-based decision model for the multi-attributes analysis by considering the concepts of intuitionistic fuzzy sets (IFSs), grey relations and compromise ratio approaches. A weighting method for the attributes is first developed based on a generalized version of the entropy and IFSs along with experts׳ judgments. Then, a new grey relational analysis is introduced to analyze the extent of connections between two potential scenarios by an intuitionistic fuzzy distance measurement. Finally, a new intuitionistic fuzzy compromise ratio index to prioritize the scenarios is proposed by considering the weight of the strategy for the maximum group utility in intuitionistic fuzzy grey environment. The feasibility and practicability of the proposed distance-based decision model is illustrated in detail, and it is implemented in a real case study to the inspection planning for the oil pump housing from Renault automobile manufacturing.

VR-PMS: a new approach for performance measurement and management of industrial systems

A new performance measurement and management framework based on value and risk is proposed. The proposed framework is applied to the modelling and evaluation of the a priori performance evaluation of manufacturing processes and to deciding on their alternatives. For this reason, it consistently integrates concepts relevant to objectives, activity, and risk in a single framework comprising a conceptual value/risk model, and it conceptualises the idea of value- and risk-based performance management in a process context. In addition, a methodological framework is developed to provide guidelines for the decision-makers or performance evaluators of the processes. To facilitate the performance measurement and management process, this latter framework is organised in four phases: context establishment, performance modelling, performance assessment, and decision-making. Each phase of the framework is then instrumented with state-of-the-art quantitative analysis tools and methods. For process design and evaluation, the deliverable of the value- and risk-based performance measurement and management system (VR-PMS) is a set of ranked solutions (i.e. alternative business processes) evaluated against the developed value and risk indicators. The proposed VR-PMS is illustrated with a case study from discrete parts manufacturing but is indeed applicable to a wide range of processes or systems.

A simulated annealing method for solving a new mathematical model of a multi-criteria cell formation problem with capital constraints

One of the most important stages in the establishment of a cellular manufacturing system is the formation of manufacturing cells in order to find out which machines dedicated to each cell and part families corresponding to these machines. In this paper, two kinds of cells are being considered: (1) general or common cells which are able to manufacture different kinds of products and (2) specific cells which are able to manufacture a specific type of product. To set up cells for manufacturing, two kinds of capital constraints are observed: (1) capital constraints for construction and formation of cells and (2) capital availability constraints for the provision of tools and equipment to manufacture corresponding commodities. To find cells and to specify the family of the assigned commodities to each cell, different and various criteria exist. In this paper, three criteria are taken into consideration simultaneously in order to minimize the sum of: (1) costs of the delay in delivering a product to costumers by the above two cells in each period, (2) costs of the common and specific cells to remain idle in each period and (3) the unused capital. Since the cell formation problem is mostly time consuming, i.e. these are NP-hard, then to solve the problem, an effective algorithm of simulated annealing (SA) method is utilized. To verify and validate the efficiency of the SA algorithm, from the standpoint of the quality of the solution obtained and time of calculations, the results obtained are compared with those of the Lingo 6 software. Results suggest that the SA algorithm have good ability of solving the problem, especially in the case of large-sized problems for which Lingo 6 cannot produce solutions.

Mathematical modelling of a robust inspection process plan: Taguchi and Monte Carlo methods

This study develops a new optimisation framework for process inspection planning of a manufacturing system with multiple quality characteristics, in which the proposed framework is based on a mixed-integer mathematical programming (MILP) model. Due to the stochastic nature of production processes and since their production processes are sensitive to manufacturing variations; a proportion of products do not conform the design specifications. A common source of these variations is maladjustment of each operation that leads to a higher number of scraps. Therefore, uncertainty in maladjustment is taken into account in this study. A twofold decision is made on the subject that which quality characteristic needs what kind of inspection, and the time this inspection should be performed. To cope with the introduced uncertainty, two robust optimisation methods are developed based on Taguchi and Monte Carlo methods. Furthermore, a genetic algorithm is applied to the problem to obtain near-optimal solutions. To validate the proposed model and solution approach, several numerical experiments are done on a real industrial case. Finally, the conclusion is provided.

Proposal for tool-based method of product cost estimation during conceptual design

Abstract The undertaken project aims at offering a support for the manufacturing cost estimation of products in the conceptual design phase. This need for dedicated tools for designers emerges from the lack of means to determinate the best technical solution that permits one to save costs and to reach safe quality. The main objective of this tool is to assist the designer in the process of manufacturing cost calculation of a product that is defined by little and inaccurate information in the preliminary design. This paper presents a procedure to develop such a tool.

Operational methods for improving manufacturing control plans: case study in a semiconductor industry

This study presents operational methods which improves tools control plan. To face challenges linked with quality, cost, cycle time, development and environment, semiconductors industries set classical process control methods. However many interactions between product-processes and tools are not exploited in practice for fine tuning controls operations and detecting premises of non conformities occurrences.

A game-based meta-heuristic for a fuzzy bi-objective reliable hub location problem

Abstract Nowadays, offering fast and reliable delivery service has become a vital issue associated with all shipment delivery systems. Due to unpredictable variability in travel times, configuration of transportation systems plays a key role in ensuring of meeting the delivery service requirement. This paper tries to investigate the effect of delivery service requirement on the configuration of the transportation system through a hub-and-spoke network. The primary goal of this paper is to study a bi-objective single allocation p -hub center-median problem (BS p HCMP) by taking into account the uncertainty in flows, costs, times and hub operations. The proposed problem is modeled through a bi-objective mixed-integer non-linear programming (BMINLP) formulation that simultaneously locates p hubs, allocates spokes to the located hubs, and assigns different transportation mode to the hub-to-hub links. Then, a fuzzy-queuing approach is used to model the uncertainties in the network. Additionally, an efficient and powerful evolutionary algorithm based on game theory and invasive weed optimization algorithm was developed to solve the proposed BS p HCMP model and obtain near optimal Pareto solutions. Several experiments besides a real transportation case show the applicability of the proposed model as well as the superiority of the proposed solution approaches compared to NSGA-II and PAES algorithms.