Showing papers in "The International Journal of Advanced Manufacturing Technology in 2009"

Additive fabrication technologies applied to medicine and health care: a review

Abstract: Additive fabrication (AF) and rapid prototyping (RP) technologies are mostly associated with applications in the product development and the design process as well as with small batch manufacturing. Due to their relatively high speed and flexibility, however, they have also been employed in various non-manufacturing applications. A field that attracts increasingly more attention by the scientific community is related to the application of AF technologies in medicine and health care. The associated research is focused both on the development of specifically modified or new methods and systems based on AF principles, as well as on the applications of existing systems assisting health care services. In this paper, representative case studies and research efforts from the field of AF medical applications are presented and discussed in detail. The case studies included cover applications like the fabrication of custom implants and scaffolds for rehabilitation, models for pre-operating surgical planning, anatomical models for the mechanical testing and investigation of human bones or of new medical techniques, drug delivery devices fabrication, as well as the development of new AF techniques specifically designed for medical applications.

Effect of welding processes on tensile properties of AA6061 aluminium alloy joints

Abstract: The present investigation is aimed at to study the effect of welding processes such as GTAW, GMAW and FSW on mechanical properties of AA6061 aluminium alloy. The preferred welding processes of these alloys are frequently gas tungsten arc welding (GTAW) and gas metal arc welding (GMAW) due to their comparatively easier applicability and better economy. In this alloy, the weld fusion zones typically exhibit coarse columnar grains because of the prevailing thermal conditions during weld metal solidification. This often causes inferior weld mechanical properties and poor resistance to hot cracking. Friction stir welding (FSW) is a solid phase welding technique developed primarily for welding metals and alloys that heretofore had been difficult to weld using more traditional fusion techniques. Rolled plates of 6 mm thickness have been used as the base material for preparing single pass butt welded joints. The filler metal used for joining the plates is AA4043 (Al-5Si (wt%)) grade aluminium alloy. In the present work, tensile properties, micro hardness, microstructure and fracture surface morphology of the GMAW, GTAW and FSW joints have been evaluated, and the results are compared. From this investigation, it is found that FSW joints of AA6061 aluminium alloy showed superior mechanical properties compared with GTAW and GMAW joints, and this is mainly due to the formation of very fine, equiaxed microstructure in the weld zone.

Quantitative models for supply chain planning under uncertainty: a review

Abstract: Managing uncertainty is a main challenge within supply chain management. Therefore, it is expected that those supply chain planning methods which do not include uncertainty obtain inferior results if compared with models that formalise it implicitly. This article presents a review of the literature related to supply chain planning methods under uncertainty. The main objective is to provide the reader with a starting point for modelling supply chain under uncertainty applying quantitative approaches. We have defined a taxonomy to classify models from 103 bibliographic references dated 1988–2007. Finally, some conclusions about the works analysed have been drawn and future lines of research have been identified.

A novel particle swarm optimization approach for product design and manufacturing.

Abstract: This paper presents a novel optimization approach that is a new hybrid optimization approach based on the particle swarm optimization algorithm and receptor editing property of immune system. The aim of the present research is to develop a new optimization approach and then to apply it in the solution of optimization problems in both the design and manufacturing areas. A single-objective test problem, tension spring problem, pressure vessel design optimization problem taken from the literature and two case studies for multi-pass turning operations are solved by the proposed new hybrid approach to evaluate performance of the approach. The results obtained by the proposed approach for the case studies are compared with a hybrid genetic algorithm, scatter search algorithm, genetic algorithm, and integration of simulated annealing and Hooke-Jeeves pattern search.

Minimal quantity lubrication-MQL in grinding of Ti–6Al–4V titanium alloy

Abstract: Titanium and its alloys are attractive materials due to their unique high strength–weight ratio that is maintained at elevated temperatures and their exceptional corrosion resistance. The major application of titanium has been in the aerospace industry. On the other hand, titanium and its alloys are notorious for their poor thermal properties and are classified as difficult-to-machine materials. The problems that arise during grinding of titanium alloys are attributed to the high specific energy and high grinding zone temperature. Significant progress has been made in dry and semidry machining recently, and minimal quantity lubrication (MQL) machining in particular has been accepted as a successful semidry application because of its environmentally friendly characteristics. A number of studies have shown that MQL machining can show satisfactory performance in practical machining operations. However, there has been few investigation of MQL grinding of special alloys like titanium alloys and the cutting fluids to be used in MQL grinding of these alloys. In this study, vegetable and synthetic esters oil are compared on the basis of the surface quality properties that would be suitable for MQL applications. The cutting performance of fluids is also evaluated using conventional wet (fluid) grinding of Ti–6Al–4V. As a result, synthetic ester oil is found to be optimal cutting fluids for MQL grinding of Ti–6Al–4V.

Material removal rate and electrode wear ratio study on the powder mixed electrical discharge machining of cobalt-bonded tungsten carbide

Abstract: In this article, a material removal rate (MRR) and electrode wear ratio (EWR) study on the powder mixed electrical discharge machining (PMEDM) of cobalt-bonded tungsten carbide (WC-Co) has been carried out. This type of cemented tungsten carbide was widely used as moulding material of metal forming, forging, squeeze casting, and high pressure die casting. In the PMEDM process, the aluminum powder particle suspended in the dielectric fluid disperses and makes the discharging energy dispersion uniform; it displays multiple discharging effects within a single input pulse. This study was made only for the finishing stages and has been carried out taking into account the four processing parameters: discharge current, pulse on time, grain size, and concentration of aluminum powder particle for the machinability evaluation of MRR and EWR. The response surface methodology (RSM) has been used to plan and analyze the experiments. The experimental plan adopts the face-centered central composite design (CCD). This study highlights the development of mathematical models for investigating the influence of processing parameters on performance characteristics.

Thermal modeling of the material removal rate and surface roughness for die-sinking EDM

Abstract: The die-sinking electrical discharge machining (EDM) process is characterized by slow processing speeds. Research effort has been focused on optimizing the process parameters so as for the productivity of the process to be increased. In this paper a simple, thermal based model has been developed for the determination of the material removal rate and the average surface roughness achieved as a function of the process parameters. The model predicts that the increase of the discharge current, the arc voltage or the spark duration results in higher material removal rates and coarser workpiece surfaces. On the other hand the decrease of the idling time increases the material removal rate with the additional advantage of achieving slightly better surface roughness values. The model’s predictions are compared with experimental results for verifying the approach and present good agreement with them.

Role of nanofluids in solar water heater

Abstract: Heat transfer enhancement in solar devices is one of the key issues of energy saving and compact designs. Researches in heat transfer have been carried out over the previous several decades, leading to the development of the currently used heat transfer enhancement techniques. The use of additives is a technique applied to enhance the heat transfer performance of base fluids. Recently, as an innovative material, nanosized particles have been used in suspension in conventional heat transfer fluids. The fluids with nanosized solid particles suspended in them are called “nanofluids.” The suspended metallic or nonmetallic nanoparticles change the transport properties and heat transfer characteristics of the base fluid. Nanofluids are expected to exhibit superior heat transfer properties compared with conventional heat transfer fluids. The aim of this paper is to analyze and compare the heat transfer properties of the nanofluids with the conventional fluids.

Application of Taguchi methods in the optimization of cutting parameters for surface finish and hole diameter accuracy in dry drilling processes

Abstract: The aim of the work reported here was to utilize Taguchi methods to optimize surface finish and hole diameter accuracy in the dry drilling of Al 2024 alloy. The parameters of hole quality are analyzed under varying cutting speeds (30, 45, and 60 m/min), feed rates (0.15, 0.20, and 0.25 mm/rev), depths of drilling (15 and 25 mm), and different drilling tools (uncoated and TiN- and TiAlN-coated) with a 118° point angle. This study included dry drilling with HSS twist drills. The settings of the drilling parameters were determined by using Taguchi’s experimental design method. Orthogonal arrays of Taguchi, the signal-to-noise (S/N) ratio, the analysis of variance (ANOVA), and regression analyses are employed to find the optimal levels and to analyze the effect of the drilling parameters on surface finish and hole diameter accuracy values. Confirmation tests with the optimal levels of machining parameters are carried out in order to illustrate the effectiveness of the Taguchi optimization method. The validity of Taguchi’s approach to process optimization is well established.

Multi-response optimization of EDM with Al-Cu-Si-TiC P/M composite electrode

Abstract: The present study investigates the relationship of process parameters in electro-discharge of CK45 steel with novel tool electrode material such as Al–Cu–Si–TiC composite produced using powder metallurgy (P/M) technique. The central composite second-order rotatable design had been utilized to plan the experiments, and response surface methodology (RSM) was employed for developing experimental models. Analysis on machining characteristics of electrical discharge machining (EDM) die sinking was made based on the developed models. In this study, titanium carbide percent (TiC%), peak current, dielectric flushing pressure, and pulse on-time are considered as input process parameters. The process performances such as material removal rate (MRR) and tool wear rate (TWR) were evaluated. Analysis of variance test had also been carried out to check the adequacy of the developed regression models. Al–Cu–Si–TiC P/M electrodes are found to be more sensitive to peak current and pulse on-time than conventional electrodes. The observed optimal process parameter settings based on composite desirability are TiC percent of 18%, peak current of 6 A, flushing pressure of 1.2 MPa, and pulse on-time of 182 μs for achieving maximum MRR and minimum TWR; finally, the results were experimentally verified. A good agreement is observed between the results based on the RSM model and the actual experimental observations. The error between experimental and predicted values at the optimal combination of parameter settings for MRR and TWR lie within 7.2% and 4.74%, respectively.

Investigation of electro-discharge micro-machining of titanium super alloy

Abstract: Being a difficult-to-cut material, titanium alloy suffers poor machinability for most cutting processes, especially the drilling of micro-holes using traditional machining methods. Although electrical discharge machining (EDM) is suitable for machining titanium alloys, selection of machining parameters for higher machining rate and accuracy is a challenging task in machining micro-holes. The present research attempts to optimize micro-EDM process parameters for machining Ti-6Al-4V super alloy. To verify the optimal micro-EDM process parameters settings, metal removal rate (MRR), tool-wear rate (TWR), over cut (OC) and taper were chosen as observed performance criteria. In addition, four independent parameters such as peak current, pulse-on time, flushing pressure, and duty ratio were adopted for evaluation by the Taguchi method. From the ANOVA and S/N ratio graph, the significant process parameters and the optimal combination level of machining parameters were obtained. It is seen that machining performances are affected mostly by the peak current and pulse-on time during micro-electro-discharge machining of titanium alloy. Mathematical models have been developed to establish the relationship between various significant process parameters and micro-EDM performance criteria. In-depth studies have also been made to examine the influence of various process parameters on the white layer and surface topography through SEM micrographs of machined micro-hole.

Grey–Taguchi method to optimize the milling parameters of aluminum alloy

Abstract: The grey–Taguchi method was adopted in this study to optimize the milling parameters of A6061P-T651 aluminum alloy with multiple performance characteristics. A grey relational grade obtained from the grey relational analysis is used as the performance characteristic in the Taguchi method. Then, the optimal milling parameters are determined using the parameter design proposed by the Taguchi method. Experimental results indicate that the optimal process parameters in milling A6061P-T651 aluminum alloy can be determined effectively; the flank wear is decreased from 0.177 mm to 0.067 mm and the surface roughness is decreased from 0.44 μm to 0.24 μm, leading to a multiple performance characteristics improvement in milling qualities through the grey–Taguchi method.

Experimental analysis of properties of materials for rapid prototyping

Abstract: Rapid prototyping (RP) can substantially shorten the time and reduce the cost of developing a new product from the initial idea to production. Rapid prototyping can help in recognizing the basic defects whose subsequent correction may prove very expensive, especially if they have already been made when the product is ready for production. There are also many restrictions of RP procedures, primarily in the number of available materials and their properties, which may differ significantly from the properties of end product materials. In this work, based on the stipulated standards of the 3D printing machines (ZPrinter 310 Plus) and the hybrid Polyjet technique (Objet Eden 330), adequate test specimens were made. Furthermore, with adequate equipment, we carried out the analysis of the dimensions, roughness of surfaces, and mechanical properties of prototype test specimens. Then, based on the data obtained by testing of properties, we provided a critical commentary regarding the data stipulated by their producers.

Optimization of pulsed GTA welding process parameters for the welding of AISI 304L stainless steel sheets

Abstract: Optimization of pulsed gas tungsten arc welding (pulsed GTAW) process parameters was carried out to obtain optimum weld bead geometry with full penetration in welding of stainless steel (304L) sheets of 3 mm thickness. Autogenuous welding with square butt joint was employed. Design of experiments based on central composite rotatable design was employed for the development of a mathematical model correlating the important controllable pulsed GTAW process parameters like pulse current (Ip), pulse current duration (Tp), and welding speed (S) with weld bead parameters such as penetration, bead width (W), aspect ratio (AR), and weld bead area of the weld. The developed models were checked for adequacy based on ANOVA analysis and accuracy of prediction by conducting a confirmation test. Weld bead parameters predicted by the models were found to confirm observed values with high accuracy. Using these models, the main and interaction effects of pulsed GTAW process parameters on weld bead parameters were studied and discussed. Optimization of pulsed GTAW process parameters was carried out to obtain optimum bead geometry using the developed models. A quasi-Newton numerical optimization technique was used to solve the optimization problem and the results of the optimization are presented.

Implementing lean manufacturing with cellular layout: a case study

Abstract: Lean manufacturing is an applied methodology of scientific, objective techniques that cause work tasks in a process to be performed with a minimum of non-value adding activities resulting in greatly reduced wait time, queue time, move time, administrative time, and other delays. In a cellular manufacturing system (CMS), machines are grouped into several cells, where each cell is dedicated to a particular part family and the objective is to maximize cell independence. CMS helps in reducing the material handling, work-in-process, setup time, and manufacturing lead time and improve productivity, operation control, etc. The facility layout used during lean implementation can be either be a line layout or in the form of cells. After grouping parts in to various part families, machine cells can be formed to produce those parts well inside the cells. As some of the lean manufacturing concepts are different from that of cellular manufacturing, e.g., establishment of Takt time, Takt-based resource balancing, etc., some new cell design methodology is required to be explored that is compatible with lean manufacturing. The rate at which work progresses through the factory is called flow rate or Takt. In the present work, a design methodology for cellular layout is proposed for implementing lean concepts and is exemplified in a manufacturing industry dealing with ammunition components for defense applications. Based on Takt time for various parts, the production flow among cells was optimized thus minimizing several non-value added activities/times such as bottlenecking time, waiting time, material handling time, etc. This case study can be useful in developing a more generic approach to design cellular layouts in lean environment.

Multi-objective production scheduling: a survey

Abstract: The real life scheduling problems often have several conflicting objectives. The solutions of these problems can provide deeper insights to the decision maker than those of single-objective problems. However, the literature of multi-objective scheduling is notably sparser than that of single-objective scheduling. Since the survey paper on multi-objective and bi-objective scheduling was conducted by Nagar et al. in 1995, there has been an increasing interest in multi-objective production scheduling, especially in multi-objective deterministic problem. The goal of this paper was to provide an extensive review of the literature on the scheduling problems with multiple objectives in the past 13 years. This paper also presents some problems receiving less attention than the others.

Application of shuffled frog-leaping algorithm on clustering

Abstract: Evolutionary algorithms, such as shuffled frog leaping, are stochastic search methods that mimic natural biological evolution and/or the social behavior of species. Such algorithms have been developed to arrive at near-optimum solutions to complex and large-scale optimization problems which cannot be solved by gradient-based mathematical programming techniques. The shuffled frog-leaping algorithm draws its formulation from two other search techniques: the local search of the “particle swarm optimization” technique and the competitiveness mixing of information of the “shuffled complex evolution” technique. Cluster analysis is one of the attractive data mining techniques which is used in many fields. One popular class of data clustering algorithms is the center-based clustering algorithm. K-means is used as a popular clustering method due to its simplicity and high speed in clustering large datasets. However, k-means has two shortcomings: Dependency on the initial state and convergence to local optima and global solutions of large problems cannot be found with reasonable amount of computation effort. In order to overcome local optima problem, lots of studies are done in clustering. In this paper, we proposed an application of shuffled frog-leaping algorithm in clustering (SFLK-means). We compared SFLK-means with other heuristics algorithm in clustering, such as GAK, SA, TS, and ACO, by implementing them on several simulations and real datasets. Our finding shows that the proposed algorithm works better than others.

Machinability investigation of Inconel 718 in high-speed turning

Abstract: Superalloy Inconel 718 is widely used for many industrial applications due to its unique properties. However, machinability of the material is considered to be poor due to its inherent characteristics. The machinability studies of Inconel 718 had been carried out by earlier researchers mostly at low or medium cutting speed. Machinability indices used in such cases have the characteristics such as cutting force, surface roughness, cutting temperature, etc. In the case of high-speed machining of Inconel 718, machinability indices such as chip compression ratio (ζ), shear angle (Ф), surface integrity, and chip analysis are of prime importance. Most of the researchers have not given due consideration to these vital machinability indices necessary for understanding of high-speed cutting of Inconel 718. In this work, an experimental investigation was carried out to understand the behavior of superalloy Inconel 718 when machined with cemented tungsten carbide (K20) insert tool. The result and analysis of this work indicated that the above-mentioned machinability indices are important and necessary to assess the machinability of Inconel 718 material effectively during high-speed machining.

Design of order picking system

Abstract: Numerous design and cost parameters, combined with an endless variety of equipment types, make it difficult to choose the right order picking system (OPS). The purpose of this study is to develop a methodology to support warehouse designers in choosing the most suitable OPS. By developing a new OPS classification, we carried out an in-depth survey on over 68 distribution centres that have been recently built in Italy. The results of the critical analysis allowed developing a design methodology to choose the most suitable OPS. This methodology has been integrated in the structured procedure for OPS design, developed by Yoon and Sharp (IIE Trans 28:379–389, 1996). Finally, a numerical case study is presented to illustrate the application of the proposed design methodology.

A CUSUM-based method for monitoring simple linear profiles

Abstract: In most statistical process control applications, the quality of a process or product is characterized by univariate or multivariate quality characteristics and monitored by the corresponding univariate and multivariate control charts, respectively. However, sometimes, the quality of a process or a product is better characterized by a relationship between a response variable and one or more explanatory variables. This relationship, which can be linear, nonlinear, or even a complicated model, is referred to as a profile. So far, several methods have been proposed for monitoring simple linear profiles. In this paper, a new method based on cumulative sum statistics is proposed to enhance monitoring of linear profiles in phase II. The performance of the proposed method is evaluated by average run length criterion. A comprehensive comparison is also conducted between the performance of the proposed method and the existing methods for monitoring simple linear profiles. The results show that the proposed method performs satisfactorily. In addition, the effects of reference value, sample size, and corrected sum of squares of explanatory variables on the performance of the proposed method are investigated.

Redesigning an assembly line through lean manufacturing tools

Abstract: The implementation of a lean manufacturing strategy represents a robust contribution to the phase sequence that leads to operational excellence and the continuous improvement through the elimination of nonvalue-added activities. Therefore, lean practices contribute substantially to plant operational performance. This paper studies the use of value stream mapping (VSM) as a tool in lean manufacturing implementation and a framework of improvement activities, in particular for an efficient introduction of kanban and milkrun techniques. A case study illustrates VSM use, as well as kanban and milkrun systems application on an assembly line. Finally, the results obtained show the path of improvement, measured through the lean rate (LR) and dock-to-dock time (DtD).

Assembly process planning and its future in collaborative manufacturing: a review

Abstract: A good assembly process plan can increase the efficiency and quality, and decrease the cost and time of the whole product manufacturing process, which is important as product and production demand changes rapidly in today’s market. Several approaches using different techniques and methodologies have been developed and reported in the literature for assembly process planning. Automated assembly process planning (AAPP) has been the main focus of the research efforts over the years, with most work concentrated on attempting to automate or to semi-automate the key sequencing process. However, some of these efforts have not been successful in general, and many assembly process plans are still based on traditional methods. The purpose of this paper is to review and outline the methodologies and tools in assembly process planning developed during the past ten years, such as the application of meta-heuristics methods to find the optimal/near optimal assembly plans and assembly line balancing, the evaluation methods for design for assembly (DFA), and collaborative assembly process planning systems. Based on this review the future trends in this area are also identified and discussed.

Reducing electrode wear ratio using cryogenic cooling during electrical discharge machining

Abstract: In this study, cooling effect of copper electrode on the die-sinking of electrical discharge machining of titanium alloy (Ti-6Al-4V) has been carried out. Investigation on the effect of cooling on electrode wear and surface roughness of the workpiece has been carried out. Design of experiment plan for rotatable central composite design of second order with four variables at five levels each has been employed to carry out the investigation. Current intensity (I), pulse on-time (ton), pulse off-time (toff), and gap voltage (v) were considered as the machining parameters, while electrode wear and surface roughness are the responses. Analysis of the influence of cooling on the responses has been carried out and presented in this study. It was possible to reduce electrode wear ratio up to 27% by electrode cooling. Surface roughness was also reduced while machining with electrode cooling.

Analysis and optimization of the ball burnishing process through the Taguchi technique

Abstract: In the present study, the analysis and optimization of the ball burnishing process has been studied. The Taguchi technique is employed to identify the effect of burnishing parameters, i.e., burnishing speed, burnishing feed, burnishing force and number of passes, on surface roughness, surface micro-hardness, improvement ratio of surface roughness, and improvement ratio of surface micro-hardness. Taguchi tools such as analysis of variance (ANOVA), signal-to-noise (S/N) ratio and additive model have been used to analyse, obtain the significant parameters and evaluate the optimum combination levels of ball burnishing process parameters. The analysis of results shows that the burnishing force with a contribution percent of 39.87% for surface roughness and 42.85% for surface micro-hardness had the dominant effect on both surface roughness and micro-hardness followed by burnishing feed, burnishing speed and then by number of passes.

Genetic-algorithm-based multi-objective optimization of the build orientation in stereolithography

Abstract: Build orientation is an important fabrication parameter in layer manufacturing (LM) since it affects the part fabrication accuracy, cost, and time. Despite its importance, orientation selection relies quite heavily on the experience and skill of the operator of the LM system, which does not guarantee optimality of the decision. In the present work, a decision support system that automates the orientation selection task is proposed. The proposed system utilizes genetic algorithms and multi-criteria optimization techniques for the definition of (near) optimum build orientation for parts fabricated with stereolithography. Build time, surface roughness, and post-processing time are considered as the main optimization criteria.

A tabu search algorithm for two-sided assembly line balancing

Abstract: Two-sided assembly lines are often used at the assembly of large-sized high-volume products, such as cars, trucks, and buses. In this type of a production line, the left side and the right side of the line are used in parallel. This paper presents a tabu search algorithm for two-sided assembly line balancing. The line efficiency and the smoothness index are considered as the performance criteria. The proposed algorithm is illustrated with two numerical example problems, and its performance is tested on a set of test problems taken from literature. The performance of the proposed algorithm is compared to the existing approaches. The computational results show that the proposed algorithm performs well.

Roughness modeling and optimization in CNC end milling using response surface method: effect of workpiece material variation

Abstract: Influence of machining parameters, viz., spindle speed, depth of cut and feed rate, on the quality of surface produced in CNC end milling is investigated. In the present study, experiments are conducted for three different workpiece materials to see the effect of workpiece material variation in this respect. Five roughness parameters, viz., centre line average roughness, root mean square roughness, skewness, kurtosis and mean line peak spacing have been considered. The second-order mathematical models, in terms of the machining parameters, have been developed for each of these five roughness parameters prediction using response surface method on the basis of experimental results. The roughness models as well as the significance of the machining parameters have been validated with analysis of variance. It is found that the response surface models for different roughness parameters are specific to workpiece materials. An attempt has also been made to obtain optimum cutting conditions with respect to each of the five roughness parameters considered in the present study with the help of response optimization technique.

In-process surface roughness prediction system using cutting vibrations in turning

Abstract: Machining is a complex process in which many variables can affect the desired results. Among them, surface roughness is a widely used index of a machined product quality and, in most cases, is a technical requirement for mechanical products since, together with dimensional precision, it affects the functional behavior of the parts during their useful life, especially when they have to be in contact with other materials. In-process surface roughness prediction is, thus, extremely important. In this work, an in-process surface roughness estimation procedure, based on least-squares support vector machines, is proposed for turning processes. The cutting conditions (feed rate, cutting speed, and depth of cut), parameters of tool geometry (nose radius and nose angle), and features extracted from the vibration signals constitute the input information to the system. Experimental results show that the proposed system can predict surface roughness with high accuracy in a fast and reliable way.

Scheduling hybrid flow shop with sequence-dependent setup times and machines with random breakdowns

Abstract: Much of the research on operations scheduling problems has either ignored setup times or assumed that setup times on each machine are independent of the job sequence. Furthermore, most scheduling problems which have been discussed in the literature are under the assumption that machines are continuously available. Nevertheless, in most real life industries, a machine can be unavailable for many reasons, such as unanticipated breakdowns, i.e., stochastic unavailability, or due to a scheduled preventive maintenance where the periods of unavailability are known in advance, i.e., deterministic unavailability. This paper deals with the hybrid flow shop scheduling problems in which there are sequence-dependent setup times, commonly known as the SDST, and machines which suffer stochastic breakdown to optimize objectives based on expected makespan. This type of production system is found in industries such as chemical, textile, metallurgical, printed circuit board, and automobile manufacture. With the increase in manufacturing complexity, conventional scheduling techniques for generating a reasonable manufacturing schedule have become ineffective. The genetic algorithm can be used to tackle complex problems and produce a reasonable manufacturing schedule within an acceptable time. This paper describes how we can incorporate simulation into genetic algorithm approach to the scheduling of a SDST hybrid flow shop with machines that suffer stochastic breakdown. An overview of the hybrid flow shops and scheduling under stochastic unavailability of machines are presented. Subsequently, the details of incorporated simulation into genetic algorithm approach are described and implemented. Consequently, the results obtained are analyzed with Taguchi experimental design.

Scheduling hybrid flowshops with sequence dependent setup times to minimize makespan and maximum tardiness.

Abstract: This article addresses the problem of scheduling hybrid flowshops where the setup times are sequence dependent to minimize makespan and maximum tardiness. To solve such an NP-hard problem, we introduce a novel simulated annealing (SA) with a new concept, called “Migration mechanism”, and a new operator, called “Giant leap”, to bolster the competitive performance of SA through striking a compromise between the lengths of neighborhood search structures. We hybridize the SA (HSA) with a simple local search to further equip our algorithm with a new strong tool to promote the quality of final solution of our proposed SA. We employ the Taguchi method as an optimization technique to extensively tune different parameters and operators of our algorithm. Taguchi orthogonal array analysis is specifically used to pick the best parameters for the optimum design process with the least number of experiments. We established a benchmark to draw an analogy between the performance of SA with other algorithms. Two basically different objective functions, minimization of makespan and maximum tardiness, are taken into consideration to evaluate the robustness and effectiveness of the proposed HSA. Furthermore, we explore the effects of the increase in the number of jobs on the performance of our algorithm to make sure it is effective in terms of both the acceptability of the solution quality and robustness. The excellence and strength of our HSA are concluded from all the results acquired in various circumstances.