Manufacturing process selection in engineering design. Part 1: the role of process selection

Whilst material selection methods are becoming mature, the selection of processes has been neglected — particularly after the preliminary design stages. This paper presents a view of current approaches to selection issues in engineering design with particular reference to process selection techniques. The need is highlighted for more focused selection techniques once a manufacturing task has been identified. A new methodology to aid the creation of task-based process selection procedures is outlined in Part 2 (A.M. Lovatt, H.R. Shercliff, J. Mater. Des., 19 (1998) 217–230).     

Nonlinear cascaded correlation processes to improve the performances of automatic spatial-frequency-selective filters in pattern recognition

A recognition process consisting of two cascaded correlation stages with a sigmoid nonlinearity applied in the first correlation plane is investigated. The filters are computed to give prespecified central correlation amplitudes in the second correlation plane when inputs are reference images. It is also desired that the second correlation amplitudes with the training images should minimize the cost function of the automatic spatial-frequency selection algorithm to reduce distortion sensitivity and to improve the performance of the filters. Filter computation methods are given, and it is shown why two such correlation processes may improve the correlation performance. Numerical simulations are described and compared with the one-stage correlation system that works with the automatic spatial-frequency selection filter.     

Selection of materials using compromise ranking and outranking methods

Selection of proper materials for different components is one of the most challenging tasks in the design and development of products for diverse engineering applications. Materials play a crucial and important role during the entire design and manufacturing process. Wrong selection of material often leads to huge cost involvement and ultimately drives towards premature component or product failure. So the designers need to identify and select proper materials with specific functionalities in order to obtain the desired output with minimum cost involvement and specific applicability. This paper attempts to solve the materials selection problem using two most potential multi-criteria decision-making (MCDM) approaches and compares their relative performance for a given material selection application. The first MCDM approach is ‘Vlse Kriterijumska Optimizacija Kompromisno Resenje’ (VIKOR), a compromise ranking method and the other one is ‘ELimination and Et Choice Translating REality’ (ELECTRE), an outranking method. These two methods are used to rank the alternative materials, for which several requirements are considered simultaneously. Two examples are cited in order to demonstrate and validate the effectiveness and flexibility of these two MCDM approaches. In each example, a list of all the possible choices from the best to the worst suitable materials is obtained taking into account different material selection criteria. The rankings of the selected materials almost corroborate with those as obtained by the past researchers.     

Sequential DOE via dynamic programming

The paper considers a sequential Design Of Experiments (DOE) scheme. Our objective is to maximize both information and economic measures over a feasible set of experiments. Optimal DOE strategies are developed by introducing information criteria based on measures adopted from information theory. The evolution of acquired information along various stages of experimentation is analyzed for linear models with a Gaussian noise term. We show that for particular cases, although the amount of information is unbounded, the desired rate of acquiring information decreases with the number of experiments. This observation implies that at a certain point in time it is no longer efficient to continue experimenting. Accordingly, we investigate methods of stochastic dynamic programming under imperfect state information as appropriate means to obtain optimal experimentation policies. We propose cost-to-go functions that model the trade-off between the cost of additional experiments and the benefit of incremental information. We formulate a general stochastic dynamic programming framework for design of experiments and illustrate it by analytic and numerical implementation examples.     

A supplier pre-selection model for multiple products with synergy effect

In practice, it is common for companies to purchase multiple products simultaneously. For the multiple required products, a large number of interested suppliers are involved. It is necessary for the purchasing company to shortlist a small number of qualified and competitive potential suppliers prior to finalising the suppliers for order fulfilment. In addition, synergy effect which is an effect arising between two or more products that produce an effect greater than the sum of their individual effects, could exist in the multi-product supplier selection environment. Since synergy effect between products can affect the choice of suppliers, it is also necessary to incorporate the synergy effect between products in the supplier selection for multiple products. However, few research efforts have been focused on the supplier pre-selection problem, let alone explicitly for multiple products with synergy effect. This paper presents a supplier pre-selection model for multiple products with synergy effect. The model is able to evaluate interested suppliers on the multiple pre-selection criteria, by the fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)-based supplier pre-selection algorithm, and shortlist a small number of potential suppliers. Illustrative examples are conducted to demonstrate the function and application of the supplier pre-selection model for multiple products with synergy effect.     

Development of a simulation-based optimisation for controlling operation allocation and material handling equipment selection in FMS

Flexible manufacturing system (FMS) is described as a set of computerised numerical controlled machines, input–output buffers interconnected by automated material handling devices. This paper develops a bi-objective operation allocation and material handling equipment selection problem in FMS with the aim of minimising the machine operation, material handling and machine setup costs and maximising the machine utilisation. The proposed model is solved by a modified chaotic ant swarm simulation based optimisation (CAS²O) while applying pre-selection and discrete recombination operators is surveyed a capable method to simulate different experiments of FMS problems. A test problem is selected from the literature to evaluate the performance of the proposed approach. The results validate the effectiveness of the proposed method to solve the FMS scheduling problem.     

An Evaluation and Proposed Modification of the Sepehri-Silver-New Heuristic for Multiple Lot Sizing Under Variable Yield

The scrap or reject allowance heuristic developed by Sepehri, Silver, and New and reported in IIE Transactions is evaluated over a wide variety of combinations of desired batch size, fixed cost, and yield. Although the procedure works, in general, better than previously developed heuristics, there are conditions — large lot size, low fixed cost, and low yield — under which it performs quite poorly.     

Flowsheet simulation of solids processes: Current status and future trends

Complex manufacturing processes are nowadays applied for production of various solid products. It is very common that for production of particles with desired properties several transformation steps like drying, milling, classification, granulation, etc. should be involved. This leads to the process structures consisting of different apparatuses or transformation substeps connected with material and energy balances. Consequently, development of new processes or optimization of already existing, as well as an optimal control, is a very challenging task, which can be partially solved using numerical modelling.For the simulation of modern production processes, the flowsheet calculations can be effectively used. Starting from the 80 s a lot of work focused on the flowsheet simulation of liquid-vapor systems has been done and as result various well-established systems exist today. With respect to the solid processes the intensive research has been started much later. In this contribution we present our view about a current role of flowsheet simulation for modeling of particulate materials and specify the open fields which can be covered in future research.     

A Diffusion Controlled Drug Delivery System for Theophylline

The goal of achieving ideal attributes of a drug delivery system including reliability and predictability has led investigators to design controlled release (CR) systems based on the principles of microporous coatings, diffusion controlled coatings and various hydrogel type systems.

In this study, the critical role of “water content fraction” of a polymer in deciding its diffusion characteristics has been ascertained and the correlation between molecular size/shape, membrane thickness, pore radii and drug diffusion has also been demonstrated. The theoretical considerations, designing and engineering of a “barrier coated-reservoir” type of a delivery system for theophylline using poly (vinyl alcohol) [PVA] as the coating material are discussed. After realizing the desired theoretical in-vitro release profile, in-vivo studies were carried out on a dog model. The potential of poly (vinyl alcohol) as a barrier coating material in developing a CR system is interestingly observed.     

A decision support system for selection of net-shape primary manufacturing processes

Developments in the capabilities of the manufacturing processes increased the number of processes that can produce a part within the requirements determined by its design and market research. The increased number of processes and unfamiliarity of manufacturing engineers to many new manufacturing processes forces the researchers to develop systematic process selection tools instead of depending on the accumulated human expertise only. In this paper, a net-shape primary manufacturing process selection decision support system (DSS), which is named PROSEL (PROcess SELection), is developed. The developed selection programme eliminates the unsuitable processes step by step by checking a part’s material, annual production quantity, specified shape, thickness and presents the most economical process as the most appropriate net-shape primary process after a final cost analysis. The developed DSS is written in Visual Studio and tested with a great deal of real-life examples. It can be concluded from the tests that the programme provides the same or better primary manufacturing process selection decisions than the practical usage, and it is a very useful support tool for net-shape primary process selections.     

Material screening and choosing methods – A review

The selection of a material for a specific engineering purpose is a lengthy and expensive process. Approximately always more than one material is suitable for an engineering application, and the final selection is a compromise that brings some advantages as well as disadvantages. One of the issues that emerges from this review is that regardless of the relation of design stages and process selection with material selection, screening and ranking are two vital steps in the material selection. A variety of quantitative selection procedures have been developed to solve this issue, so that a systematic evaluation can be made. This paper seeks to address the following questions: (1) what is the contribution of the literature in the field of screening and choosing the materials? (2) What are the methodologies/systems/tools for material selection of engineering components? (3) Which approaches were prevalently applied? (4) Is there any inadequacy of the approaches? This research not only provides evidence that the multi-criteria decision making approaches has the potential to greatly improve the material selection methodology, but also aids the researchers and decision makers in applying the approaches effectively.     

Cumulative conformance count chart with sequentially updated parameters

The Cumulative Conformance Count (CCC) chart has been used for monitoring processes with a low percentage of nonconforming items. However, previous work has not addressed the problem of establishing the chart when the parameter is estimated with a prescribed sampling scheme. This is a prevalent problem in statistical process control where the true values of the process parameters are not known but it is desired to determine if there have been drifts since process start-up. This situation is also not well-covered by the conventional CCC chart, which generally assumes known process parameters. In this paper, we examine a sequential sampling scheme for a CCC chart that arises naturally in practice and investigate the performance of the chart constructed using an unbiased estimator of the percent nonconforming, p. In particular, we examine the false alarm rate and its intended target as well as deriving the mean and standard deviation of the run length; and compare the performance with that established under a binomial sampling scheme. We then propose a scheme for constructing the CCC chart in which the estimated p can be updated and the control limits are revised so that not only the in-control average run length of the chart is always a constant but it is also the largest which is not the case for the CCC chart even when the true p is known. It is shown that the proposed scheme performs well in detecting process changes, even in comparison with the often utopian situation in which the process parameter, p, is known exactly prior to the start of the CCC chart.     

Autombile bumper standoff and collision repair cost

Measurements were made on thirty-six 1977–1980 cars concerning the relative placement of certain components known to exhibit high collision repair cost. The intention was to help identify car features that increase collision repair cost. The measurements were developed from a concept termed BUMPER STANDOFF, defined as the shortest head-on distance from the bumper (either the inner edge, or the reference barrier placed at the outer edge, perpendicular to the car's longitudinal axis, depending on the component distance being measured) to specific components exhibiting high repair cost or frequency. High correlations in the range of r = 0.47–0.82 (p < 0.05-< 0.01) were found between the front fender standoff distance and headlamp standoff distance vs. claim cost and claim frequency. The first structure likely to be impacted for our overall sample in a simple head-on collision, after the bumper, was the headlamp(s), front fender, hood, or grille, with correlations between 0.48 and 1.00 (p < 0.05-0.00). The front fender was singled out among the subcompacts, while the grille predominated for the compacts and intermediates (r = 1.000, p = 0). Results from these laboratory measurements are essentially in agreement with those results obtained from actual crashes in other studies. That is, they all share very high damage frequency and claim or repair cost rankings for the front fender and headlamp(s). Likewise, measurements relating to the first structure impacted, after the bumper, hold promise as predictors of component damage frequency and claim frequency, in relation to headlamp, front fender, and possibily hood and grille measurements. Bumper standoff measurements are proposed as useful indications of a passenger car's damageability in low speed collisions.     

Economic and environmental analysis of PHAs production process

Following the growing demand to improve both economic and environmental performance of PHAs production, the research focused on the evaluation of the economic and environmental performance of PHAs production process via aqueous two-phase extraction (ATPE). Thus, the process analysis of two processes with different PHAs purification and recovery strategies (which are with and without thermoseparating ATPE as primary purification step) was performed. Using the basis of 9000 tons PHAs production per year and 7920 operating hours, the process with thermoseparating ATPE as primary purification step standout in terms of both economic and environmental performance. PHA production cost of 5.77 US$/kg with a payback period of fewer than 4 years and ROI of 25.2% was achieved. The results showed that most of operating cost is contributed by facility-dependent cost and raw material cost, while the main contributor to raw material cost is carbon source. The insight from sensitivity analysis has demonstrated that the economic performance is sensitive to the fluctuation in surfactant cost. This proved that utilizing thermoseparating ATPE as primary recovery step not only helps to reduce chemical consumption, it also minimizes downstream equipment cost and wastewater treatment cost.     

Development of an integrated model for process planning and parameter selection for machining processes

The concept of ‘do it right the first time’ in the machining industry not only expects the best quality products but also at the best possible cost. The cost of machining depends on intelligent process planning and selection of machining parameters such as speed, feed, and depth of cut. The problem of machining parameter selection has received great attention by researchers and many techniques have been developed. A review of these techniques reveals that the selection of the machine and cutting tool is done before the process of cutting parameter selection and process sequencing, and often the selection is based on experience. The current research is an attempt to develop an integrated model (ExIMPro: Expert system based Integrated model for Machining Processes) which finds the sequence of operations with set of machines, tools, and other process parameters to minimise the cost of machining for a cylindrical part. This system consists of existing expert system Machining Parameter SELection (MPSEL) for machine and tool selection and a Microsoft Excel® and Visual Basic® based parameter selection model. The present model focuses on turning and cylindrical grinding operations but other processes can be incorporated with little modification to the software.     

EXCITE: Expert consultant for in-plant transportation equipment

The cost of handling material is a vital factor in the facilities design process, whether it is for a new facility or for the redesign of an existing facility. Handling activities generally account for 30 to 40% of production costs, but in some industries they can be as high as 70%. Well designed handling systems are thus crucial for reduced costs and increased profits.

A key task in the material handling system design process is the selection and configuration of equipment for transport and storage in a facility. Material handling equipment selection is a complex, tedious task, and there is usually more than one good answer for any particular situation. A number of good quantitative techniques are available to aid the industrial engineer in determining layout design with the aim of reducing material handling cost. Unfortunately, there are few tools other than checklists to aid the engineer in the selection of appropriate, cost-effective material handling equipment. Analytical models are not often applied in industry because they generally consider only quantifiable factors such as cost and utilization and are difficult to implement.

This paper describes a knowledge-based approach for addressing the major factors that influence equipment selection. The research effort involved two major activities: compilation of a knowledge base from an in-depth review and modification of traditional checklists and published literature on equipment selection; and development of a prototype expert system for material handling equipment selection.     

Multivariate tolerance design using quality loss

The determination of tolerance allocations among design parameters is an integral phase of product/process design. Such allocations are often necessary to achieve desired levels of product performance. We extend our prior research on tolerance allocation by developing both parametric and nonparametric methods for a multivariate set of performance measures that are functions of a common set of design parameters. The parametric method is novel and assumes full information about the probability distribution of design parameter processes. The proposed nonparametric method assumes that only partial information is available and significantly extends prior research by considering a more contemporary and realistic model for manufacturer costs. For both methods we derive economically based models that represent the costs, both internal (supplier) and external (manufacturer), of tolerance allocation under several different process scenarios. These scenarios are based on the manner of disposition of nonconforming product. For the parametric methods we derive tolerance allocation solutions that jointly minimize expected total cost of the supplier and manufacturer. For the nonparametric methods we derive solutions for tolerance allocation that jointly minimizes the maximum expected total cost. An example in the fabrication of a rubber tread compound is used to: (i) demonstrate the implementation of our proposed methodologies for tolerance allocation; (ii) illustrate and compare the nonparametric and parametric methods; land iii) assess the sensitivity of optimal tolerance allocations to changes in process model types, cost coefficient estimates, and manner of disposition of nonconforming product.     

Design, processing and cost considerations in materials substitution

Materials substitution should be performed as part of an integrated activity where redesign, processing and cost are analysed simultaneously. The paper illustrates this approach by analysing the substitution of the material of a steam control valve gate. The selection is narrowed to two candidate materials, each with its alternative design and sequence of manufacturing processes. A simpler design requiring a less complex manufacturing sequence is associated with the Haynes Alloy R-41, thus making it economically more attractive than type S42200 stainless steel, which requires a more complex design and manufacturing sequence. However, there has been no experience of using the Haynes Alloy as valve gate material.     

Solving Quadratic Assignment Problems by 'Simulated Annealing'

Recently, an interesting analogy between problems in combinatorial optimization and statistical mechanics has been developed and has proven useful in solving certain traditional optimization problems such as computer design, partitioning, component placement, wiring, and traveling salesman problems. The analogy has resulted in a methodology, termed “simulated annealing,” which, in the process of iterating to an optimum, uses Monte Carlo sampling to occasionally accept solutions to discrete optimization problems which increase rather than decrease the objective function value. This process is counter to the normal 'steepest-descent' algorithmic approach. However, it is argued in the analogy that by taking such controlled uphill steps, the optimizing algorithm need not get “stuck” on inferior solutions.

This paper presents an application of the simulated annealing method to solve the quadratic assignment problem (QAP). Performance is tested on a set of “standard” problems, as well as some newly generated larger problems (n = 50 and n = 100). The results are compared to those from other traditional heuristics, e.g., CRAFT, biased sampling, and a revised Hillier procedure. It is shown that under certain conditions simulated annealing can yield higher quality (lower cost) solutions at comparable CPU times. However, the simulated annealing algorithm is sensitive to a number of parameters, some of whose effects are investigated and reported herein through the analysis of an experimental design.