Search

The reliability allocation of machine tools which is a multi-attribute decision-making problem has great significance in designment of machine tools. This paper integrates the intuitionistic trapezoidal fuzzy numbers and performance sorting technique based on similar ideal solutions to achieve the flexible allocation of machine tools reliability. Firstly, intuitionistic trapezoidal fuzzy numbers are employed to integrate decisions made by multiple decision-makers and fuzzy information of their preferences. Then, intuitionistic trapezoid fuzzy numbers' expectations are treated as the weights of criteria. Finally, performance sorting technique based on similar ideal solutions is used to obtain the reliability allocation weight of every subsystem. To investigate the efficacy and simplicity of the provided approach, reliability distribution in a CNC machine tool is introduced as an example to explain its specific contents. It can be concluded that the provided method is more precise and convenient by comparing the results of this approach with those obtained by analytic hierarchy process method. [ABSTRACT FROM AUTHOR]

Although there are many types of cutting tool materials, no single cutting tool material meets all the needs of machining applications because of the complex and changeable cutting conditions. It is crucial to study the matching between tool materials and workpiece materials for improving productivity, obtaining good surface quality and reducing machining cost. In this paper, rule-based reasoning (RBR) method and gray complex proportional assessment (COPRAS-G) method are applied to solve the problem of cutting tool material selection. RBR is used for primary selection of tool materials to reduce the number of alternatives and the computational complexity in COPRAS-G method. Ten attributes of tool materials including physical, mechanical, chemical, and cost parameters are selected as criteria in the COPRAS-G method, and entropy method and analytic hierarchy process (AHP) are used to determine the objective weights and subjective weights of attributes, respectively. Finally, the ranking of several alternatives is obtained to select the most suitable cutting tool material. Taking the cutting tool material selection of machining CGI as an example to validate the method proposed in this paper. The research results revealed that the alumina ceramic has the best comprehensive performance, alumina ceramic cutting tools containing carbides to improve the flexural strength and fracture toughness, or cemented carbide cutting tools with alumina coating are preferred for machining CGI. High-speed milling experiments of CGI were carried out, and the results showed that the alumina-coated tungsten carbide tools had longer tool life than the silicon nitride ceramic tools, which confirmed the effectiveness of the proposed cutting tool material selection method. And this method can be extended to other engineering applications in material selection problems. [ABSTRACT FROM AUTHOR]

This paper deals with an integrated design approach for additive manufacturing (AM), as a design for additive manufacturing (DfAM) approach. This DfAM approach focuses on two important activities of manufacturability analysis, as well as material and process selection in the concept of concurrent engineering and integrated design approach (CE/ID). It could be considered as a guideline for the researchers in the early phase of the product development process. For this purpose, a novel process and resource selection problem for AM is formalized as an additive manufacturing process and resource selection problem (AMPRSP). This problem is defined to investigate simultaneously the manufacturability, and process and resource selection issues for AM. A multi-criteria evaluation system (MCES) is proposed to solve this problem by evaluating the manufacturability of the product, and selecting the AM resources. Firstly, the AM process, machine, and material are explored and selected regarding technical and economic evaluation criteria. Then, the most appropriate alternative for fabrication with AM is selected by considering the sub-criteria including build time, accuracy performance, and cost. To solve this multi-criteria problem, an analytic hierarchy process (AHP) method is employed. Overall, this evaluation system is a step-by-step methodology that includes screening, comparative assessment, and a ranking process to select the most suitable alternative for AMPRSP. Finally, the proposed approach is illustrated by an industrial case study. [ABSTRACT FROM AUTHOR]

Motivated by a real-world material handling system selection problem, this paper proposes a framework that allows for quantifying safety and incorporating it in multi-criteria decision-making processes that involve both quantitative and qualitative measures. In the proposed framework, the results of failure mode and effect analysis (FMEA) for each alternative are converted into a quantitative measure of total safety and reliability associated with that alternative. A modified analytic hierarchy process (AHP) that differentiates between subjective and objective measures is then used to compare the alternatives at hand. In this modified AHP, experts' judgments are used for pairwise comparison of alternatives with respect to qualitative measures, while for quantitative criteria, measured or estimated performance is directly used to obtain the required pairwise comparisons. An Excel-based decision support tool that implements the proposed framework is developed and made available online for researchers and practitioners. An application based on a real-world problem in an injection molding facility is also presented. [ABSTRACT FROM AUTHOR]

Repeated positioning accuracy, axial stiffness, cutting vibration, and rotation noise are key indexes that affect the comprehensive performance of computer numerical control (CNC) servo turrets. In order to evaluate the comprehensive performance of CNC servo turrets accurately, a new evaluation method is proposed based on accuracy retentivity theory in this paper. The retentivity degree evaluation methodology of performance indexes of the turret based on error threshold and 3δprinciple are proposed. Analytic hierarchy process (AHP) is used to calculate the weight of the influence degree on the turret, and the comprehensive performance retentivity degree of the turret is obtained. A comprehensive performance degradation model is established by using least squares. Finally, the comprehensive performance tracking test and analysis are conducted by taking two turrets as an example. The degradation law of the comprehensive performance retentivity degree of turrets is obtained, and the remaining performance retentivity time is predicted. [ABSTRACT FROM AUTHOR]

The evolving technology of additive manufacturing (AM) is posing novel challenges in manufacturing practice since nowadays functional, end-use components, and assemblies are produced by commercially available AM equipment. In order to safeguard the functionality and the interchangeability of a part, the designer must clearly denote a set of Geometrical Product Specifications (GPS) in the 3D model or in the engineering drawing by using the existing standards, e.g., ISO 1101, ISO 5459, and ISO 1660. Apparently, the family of ISO GPS standards that are currently used in design, manufacture, and verification has been developed so as to address the needs of traditional manufacturing processes rather than AM. Supported by numerous recent publications, the argument that current standardization does not sufficiently support the geometrical specification and verification of AM parts is getting more and more popular. The paper investigates and questions the need for the development of AM process-specific standards, related to the tolerancing and verification of mechanical components, as encountered with castings, forgings, and composites. Focusing on the most critical issue of datum establishment and datum hierarchy, the capability of existing tolerancing tools, as provided by the ISO GPS standards, to serve the process-specific AM needs is systematically examined. Moreover, major AM process-specific parameters such as build direction, layer thickness, support structure, and hatching plan are linked with the datum system designation and datum hierarchy tasks through a design case study and analysis. The major findings of this research pointing towards the establishment of AM-specific design-for-accuracy good practices are presented and discussed. [ABSTRACT FROM AUTHOR]

The sustainable management of wastes has attracted in the last decades an increasing number of industrial actors, policymakers and researchers. Environmental improvements, social responsibilities and economic opportunities led many manufacturers to implement different kinds of end-of-life (EoL) strategies. However, in many cases, these strategies are not supported by a correct commitment of top managers, but are implemented only in response to competitor's actions. This paper aims to improve the understanding of management practices concerning remanufacturing activities. A mixed evaluation model based on strengths, weaknesses, opportunities and threats (SWOT) analysis and Analytic Hierarchy Process (AHP) is proposed. Its final aim is the evaluation of top management commitment in driving remanufacturing as an overall sustainable initiative into three different sectors (automotive, aerospace and medical equipments). The survey allowed to define the most critical factors for each sector and, so, to analyse underlying remanufacturing strategies. [ABSTRACT FROM AUTHOR]

In the aircraft industry, three-dimensional (3D) printing can confer several benefits, such as shortened cycle times, reduced production costs, and lighter part weights. However, some concerns must be addressed for 3D-printing applications to be viable. This paper investigated these concerns by reviewing the current 3D printing practices in the aircraft industry. The literature review identified five factors critical to the applicability of advanced 3D printing technologies to the aircraft industry, and a fuzzy systematic approach was applied to assess the applicability and relative importance of the identified factors, combining fuzzy geometric mean and fuzzy analytical hierarchy process. The findings provide valuable input for countries or regions considering expanding 3D printing applications to their aircraft industries. [ABSTRACT FROM AUTHOR]

In precision machine assembly process, the product quality is not only dependent on the tolerance design, but also on the assurance of the assembly process planning. Therefore, there is a need to develop a mathematical analysis method to predict and control the variation in an assembly process. In this paper, to improve assembly precision and finally improve assembly quality stability for machining products, a mechanical assembly accuracy prediction model based on a state space equation is put forward. In this approach, fuzzy analytical hierarchy process (FAHP) is used to identify the key factor affecting the product quality. With the help of current variation of assembling process, the state space equation is used to build the variation propagation model of a mechanical assembly system, predict the influence law of machine precision, and guarantee the machine assembly precision within the boundary. Finally, the validity is verified by using the application of the small six-axis precision machine tool. [ABSTRACT FROM AUTHOR]

Cloud manufacturing has experienced a rapid development in the past several years. The research on its theories, technologies, and applications still keeps attracting attentions from more and more researchers. One of the most important issues to its improvements and quality of manufacturing service is the optimization of value network. This paper researched the optimization method of cloud manufacturing value network based on the Analytic Hierarchy Process (AHP) method and the dynamic programming of business decisions computing model. According to the function of decision-making model, this paper used the AHP and dynamic programming method to establish the mathematical model of cloud manufacturing service value network for seeking the best value chain, and on this basis, established a different model to get the optimal result under the different conditions by time, cost, and resources. [ABSTRACT FROM AUTHOR]

Machining of aircraft structural components can waste up to 90% of the raw material. Therefore, evaluation of alternative manufacturing processes for those components is crucial for reducing the economic and environmental impacts of manufacturing. As the shape and material of a component must match the manufacturing process used, it is necessary to perform a redesign for manufacturing in order to compare manufacturing processes accurately. In this paper, an integrated material-design-process selection methodology is developed. Topology optimization, design for manufacturing (DFM) and design for additive manufacturing (DFAM) are used to design components satisfying the same functional requirements but shaped using different manufacturing processes. New selection criteria such as part weight and buy-to-fly ratio are used to rank material-design-process triplets with the analytic hierarchy process (AHP). The proposed methodology is applied to redesign an aircraft component for machined Al7075-T6 and the same component for selectively melted AlSi10Mg powders. Even though the yield strength of Al7075-T6 is 40% greater than that of AlSi10Mg, optimized components for machining and selective laser melting meet the yield strength security factor while remaining competitive in terms of mass. Although the selective laser melted component is about seven times more expensive to produce than the machined one, it remains competitive considering functional and economic criteria. [ABSTRACT FROM AUTHOR]

Single point incremental forming (SPIF) is a promising manufacturing process, but its industrial implementation is hindered by the lack of computer-assisted tools. CAD/CAM solutions which can be directly applied for other machining processes (milling) can hardly be used for SPIF. This paper emphasizes some particularities of using CAD/CAM (computer-aided design/computer-aided manufacturing) tools for SPIF and analyze six CAM-based processing strategies, based upon different toolpaths. The proposed strategies are compared with regard to formability and accuracy of the machined parts, processing time, surface quality, and ease of toolpath generation. Finally, an analytic hierarchy process (AHP) technique, based upon the experimental results, is used for selecting the best processing strategy. The results of the AHP have indicated as the best choice a two-stage processing strategy, involving a roughing stage and a two-pass finishing stage. [ABSTRACT FROM AUTHOR]

Environmental factors have a major role in selecting an optimal process planning schema. However, the systems that are currently available are barely capable of dealing with these environmental issues. In this paper, an automated evaluation tool based on environmental standards has been developed so that it is capable of identifying and quantifying the environmental impacts of a set of feasible manufacturing process plans and is able to select a near-optimal solution (out of the feasible set) for a desired process plan of a given part. The selection methodology is based on the analytic hierarchy process (AHP) and has considered three main factors: emission, waste production, and hazardous materials to arrive at a selection. The proposed technique has been written in detail in the following paper and has been illustrated with appropriate case studies. [ABSTRACT FROM AUTHOR]

Supplier selection is one of the critical problems in supply chain systems. Within the last decades, by the emergence of sustainability concept, companies have been motivated to enhance their supplier's sustainability and move toward sustainable development. This paper proposes a structured and integrated decision model for evaluating sustainable suppliers in the context of telecom industry by combining analytical hierarchy process (AHP) and improved grey relational analysis (IGRA) approaches. The proposed model employs AHP for calculating sustainability criteria weights and IGRA for ranking suppliers. Moreover, a sensitivity analysis is also performed to demonstrate the robustness of the model. In this research, the sustainable supplier selection problem of the telecom industry in the southern part of Iran was investigated, showing the effectiveness and applicability of this proposed integrated approach. [ABSTRACT FROM AUTHOR]

Supplier selection is a crucial multi-criteria decision-making (MCDM) problem which requires a tradeoff between multiple criteria denoting vagueness and imprecision with the involvement of a group of experts. Fuzzy MCDM methods allow for modeling the decision processes involving imprecise and subjective information expressed as linguistic variables or fuzzy numbers by decision-makers. In this paper, considering information fusion between criteria and linguistic terms, a robust supplier selection algorithm based on the hybrid use of a modified fuzzy Analytic Hierarchical Process (FAHP) and generalized Choquet fuzzy integral (GCFI) methods is proposed. The FAHP is employed in order to obtain importance weights of the evaluation criteria and then the GCFI is used to achieve the overall performance values of supplier alternatives. The suggested methodology has been conducted in a real case application for supplier selection problem in a steel-producing company operating in Turkey. We also showed the robustness of the devised methodology through a sensitivity analysis and compared the obtained results with other MCDM methods. Consequently, it is concluded that the proposed integrated approach can effectively handle supplier selection and other MCDM problems especially when there are interdependent sub-criteria in a complex hierarchy of evaluation criteria. [ABSTRACT FROM AUTHOR]

During the design process of product-service systems (PSS) particular attention must be placed on sustainability, since the current models do not completely support the generation of sustainable PSS solutions. New methods to investigate PSS requirements analysis, evaluation, and conceptual design stages according to sustainability principles are needed. In this paper, an approach based on quality function deployment (QFD) is proposed to support PSS design. QFD is applied to translate stakeholders' requirements in the three sustainability dimensions into engineering metrics of products and services. QFD is also applied to deploy PSS functions and to support the conceptual development. Fuzzy analytic hierarchy process (FAHP) is used to prioritize the stakeholders' requirements in the three sustainability dimensions, and the fuzzy set theory is considered to reduce the vagueness and uncertainty during the process. The proposed approach is applied in an illustrative case for the conceptual design of a bike-sharing system. The suggested approach aims to contribute to the theory development as well as for practitioners. Firstly, it allows integrating the sustainability principles since the requirements elicitation stage, considering all stakeholders involved in the offer. Secondly, the requirements evaluation considering FAHP allows prioritizing the sustainability requirements dealing with uncertainty and vagueness. Finally, it helps to obtain more realistic results by integrating fuzzy decision-making into QFD. In future research, the integration of the Theory of Inventive Problem Solving (TRIZ) in the proposed approach will be investigated as well as the evaluation of different PSS concepts according to their sustainability potential. [ABSTRACT FROM AUTHOR]

The ability of managing a production system is an essential factor for maintaining the position in the market. Companies are constantly looking for optimizing their process in order to follow this dynamic competition. In this sense, different tools and methodologies are applied in order to support the decision-making, based on algorithm solutions and objective results. Regarding that, this paper presents an analysis of the best alternatives to eliminate productive process bottlenecks of martensitic stainless steel (AISI-420) of a metal-mechanics industry from South of Brazil by applying the analytic hierarchy process (AHP). The results indicate the best alternative to extinguish the production process bottleneck as the replacement of the material of the polishing rolls, from sisal to cotton, which represents 27.1 % of preference regarding all the alternatives. Following it is the increase of speed of the conveyors and the verification and substitution of industrial squirts, all of them with relative high impact on the solution of the problem. Based on the changes made, it is possible to notice great reduction in losses and reprocess, besides the improvements pointed out by the inspection and quality sector. Considering all the improvements, the results show 74 % of efficiency when compared to the previous situation. [ABSTRACT FROM AUTHOR]

Cutting tools are the executor and core element of machining, and tool materials are of decisive significance for the development of high-speed machining technology. For a particular workpiece material, to select the appropriate tool material is an important prerequisite to increase the machining productivity and to improve the machined surface quality. In this paper, a compromised weighting method composed of the subjective judgment method and the objective judgment method was utilized to conduct criterion weighting in the cutting tool material selection when machining Al-Si piston alloy. The analytic hierarchy process (AHP) method was used to subjectively judge the significance of the material properties and determine their criterion weight, while the entropy weight method was adopted to objectively judge the significance and determine their weight values. The synthesis weights of the material properties were determined by the comprehensive assessment of both the AHP and entropy methods, and the synthesis scores of the different tool material candidates were obtained. Results revealed that PCD was found as best materials for Al-Si piston alloy machining, and YG8 is slightly more suitable than YG6X for machining Al-Si piston alloy. In short, the qualitative problems in tool material selection were realized systematically and hierarchically by quantitative calculation and analysis. This provides a new thinking in tool material selection for high-efficiency machining of difficult-to-machine materials. [ABSTRACT FROM AUTHOR]

Equipment selection is a complex task that requires the consideration of multiple criteria with different measurement units. A number of decision-making methods have been proposed for analysing equipment selection problems, each having their own distinctive advantages and limitations. Despite the number of decision-making techniques available, few comparative studies exist that evaluate two or more methods with a singular problem. This paper evaluates three multi-attribute decision-making methods for an equipment selection problem in the early stages of a chemical manufacturing process. A software framework which incorporates analytical hierarchy process (AHP), multi-attribute range evaluations (MARE) and ELimination Et Choix Traduisant la REalité trois (ELECTRE III) was developed and distributed to a technology manager at Fujifilm Imaging Colorants Ltd (FFIC). The manager, within a team of nine people, examined the same decision problem using the three decision analysis methods. The results of the study are examined in respect to assessing each method's ability to provide accurate representations of the decision-makers' preferences and the ability to comprehend the uncertainty present. The decision-makers identified MARE as their preferred method, AHP was found to be comparatively more time-consuming and showed the highest variation of results while ELECTRE III was unable to provide a conclusive best result. [ABSTRACT FROM AUTHOR]

A virtual enterprise (VE) is a platform that enables dynamic collaboration among manufacturers and service providers with complementary capabilities in order to enhance their market competitiveness. The performance of a VE as a system depends highly on the performance of its partner enterprises. Hence, choosing an appropriate methodology for evaluating and selecting partners is a crucial step toward creating a successful VE. In this paper, we begin by presenting an extensive review of articles that address the VE partner selection problem. To fill a significant research gap, we develop a new goal programming (GP)-based approach that can be applied in extreme bidding conditions such as tight delivery timelines for large demand volumes. In this technique, fuzzy analytic hierarchy process (F-AHP) is used to determine customer preferences for four main criteria: proposed unit price, on-time delivery reliability, enterprises' past performance, and service quality. These weights are then incorporated into the GP model to evaluate bidders based on customers' preferences and goals. We present a case study in which we implement the F-AHP-GP technique and verify the model's applicability, as it provides a more flexible platform for matching customers' preferences. [ABSTRACT FROM AUTHOR]

Design optimization of mechanical properties is one of the most challenging tasks in the design and development of new tool materials for diverse machining applications. Mechanical properties of tool material play a crucial role during the entire tool design and machining process. This paper attempts to solve the optimization problem of mechanical properties for AlO-based ceramic tool material in turning of ultra-high-strength steel 300M. First, a high-speed turning experiment was conducted to explore the effect of various mechanical properties of ceramic tool materials on tool life, and then an exponential model was built to decompose the tool life for obtaining the best comprehensive mechanical properties of ceramic tools. Second, analytic hierarchy process (AHP) method combined with Criteria Importance Through Intercriteria Correlation (CRITIC) method was used to optimize the mechanical properties of ceramic tool materials. The optimization results of hardness, fracture toughness, flexural strength, and Young's modulus were 21.3 GPa, 8.9 MPa·m, 898.6 MPa, and 473.5 GPa, respectively. Finally, under the guidance of optimization results, AlO/TiC/TiN ceramic tool (AT10N20) materials were fabricated to turning of ultra-high-strength steel 300M. The cutting performance and wear mechanisms of ceramic tool AT10N20 were investigated. The experimental results indicated that the design optimization method could be useful for designing and developing new tool materials in specific machining applications. [ABSTRACT FROM AUTHOR]

Belt grinding is a widely adopted method in processing titanium alloy materials. However, its unique grinding mechanism will greatly affect grinding efficiency. Meanwhile, in order to finish processing task, adopting the method of replacing belts frequently will further make processing time, cost, and energy consumption rise, as well as the pollution during the whole processing. Considering the problems above, first, establish a multi-objective optimization model, which takes spindle rotary speed, feed speed of workpiece, grinding depth, and axial feed as the variables and takes processing time, SEC (specific energy consumption), cost, and environmental impact as objective optimization functions. Secondly, multi-objective particle swarm optimization algorithm is applied to solve resources allocation objectives for Pareto optimal solutions. Then, analytic hierarchy process is applied to analyze the degree of environmental impact of each solution among Pareto optimal solutions and finalize the best optimization solution of belt grinding. Finally, an experiment case is performed to verify the effectiveness of the optimization model. The result shows that, compared with experience-guided parameters, the optimized grinding parameters make processing efficiency improve by 17.3% and SEC declines by 13.2% cost decline by 17.0%. The proposed optimization method of grinding parameters is effective and can be applied to engineering practice. Meanwhile, it can provide a reference to the selection of grinding processing parameters. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) has been used to produce complex parts usually in small batch sizes. Recently, AM has been gaining importance with the development of new production technologies encompassing a wider range of materials. These new technologies allow broader AM application in the industry, beyond traditional usage in rapid prototyping. As a result, the number of parts being produced by AM technologies has been increasing. The differences among AM production technologies and the specific capabilities and restrictions of each available manufacturing machine result in complex manufacturing process definition. Moreover, process technology knowledge in the area is still limited to few professionals. In order to support process manufacturing to evaluate which AM technology would be best suited to produce a particular part, this paper presents a method for selecting the AM process based on the technical specifications of a part. The method relies on Analytic Hierarchy Process (AHP) to rank the most appropriate technologies and machines. Relevant parameters of the main machines available in the market were raised. These parameters are considered in the selection of machines able to produce a particular part considering its specifications. Practical applications of the method resulted in adequate responses to support manufacturing process definition. [ABSTRACT FROM AUTHOR]

Manufacturing capability of a firm is given by the level of output generated by the production system employed which in turn decides the competitiveness in the market. The pattern of structural and infrastructural decisions in the manufacturing affects the capability of the production system. Therefore, it is crucial to know the overall manufacturing capability of a firm and the contribution of each decision in it. This paper presents quantification of manufacturing capability based on multi-criteria approach. A total of 33 decisions (criteria) and their corresponding choices have been identified from the literature analysis to quantify the manufacturing capability. These decisions are then classified into six decision areas (group criteria), and the manufacturing capability evaluation problem is modeled by using analytical hierarchy process (AHP) framework. The approach facilitates computation of manufacturing capability index by evaluating the decisions taken in the manufacturing, which is then mapped into four levels, namely, infant, industry average, adult, and world class as proposed by the Miltenburg. The methodology is illustrated with a numerical example for a job shop manufacturing system. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) has become an important agenda in the advanced manufacturing environment. In order to encourage IoT application and assure an appropriate selection of processes to be improved by IoT technology, a group of analysis criteria must be highlighted to give the companies a tool to perform the correct selection. This study aims to propose a model for selecting IoT technology. The research design combines a systematic literature review, applying bibliometrics and content analysis, with case application and refinement. An application was carried out in an IoT hardware company, incorporating it at a solvent recycling machine. A second application was performed in a seedling selection machine producer. As a result, a model for selecting IoT technology is presented, which consists of four phases—process modeling, grading, weighting, and final selection. The model applies an analytic hierarchy process (AHP) based on the following criteria: reliability, security, business, mobility, and heterogeneity. The results also suggest IoT selection is related to the ability of combining different criteria related to the system and technology selection to install IoT solutions. Finally, issues related to the system characteristics other than technology are becoming more cited in the literature in the last 5 years concluding that selecting IoT technology is a complex activity that needs to be improved, especially in the years to come. [ABSTRACT FROM AUTHOR]

In the reliability optimization design field of CNC machine tools, reliability allocation plays a significant part, which has the characteristics of high complexity and strong uncertainty. Traditionally, reliability allocation methods have the disadvantages of a single allocation influence factor, too subjective or too objective, not flexible enough, etc. To solve the related problems, a novel reliability allocation method for machine tools is proposed, which combines subjective and objective weightings, and a variety of influencing factors are considered comprehensively. To deal with the characteristic of uncertainty and fuzziness in machine tool reliability analysis, different intuitionistic trapezoidal fuzzy numbers (ITrFNs) are allocated according to the importance of influencing factors. As the subjective method, the analytic hierarchy process (AHP) can reflect the decision maker's subjective preferences of machine tool influence factors, while the grey relational method (GRA) can analyze the relationship between data which is adopted as an objective weighting method. The reliability of each subsystem is obtained by combining the two methods. Finally, the validity of the proposed method is proved by an illustration analyzing and comparing it with the traditional AHP method and fuzzy allocation methods. [ABSTRACT FROM AUTHOR]

The reconfigurable manufacturing system (RMS) meets the challenges of dynamic customer demands, technological advancements, and reducing lead time, among other things. It was necessary to have a framework that can assist in increasing RMS adoption as well as evaluating its performance. The present study seeks to develop a hybrid framework for prioritizing performance metrics of RMS that helps the designers of the manufacturing system in decision making. A total of 31 enablers for RMS were identified through a literature review, the weight of each enabler was computed by the fuzzy-AHP (analytic hierarchy process) method, and the fuzzy-TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method was used to prioritize 22 performance metrics of RMS. According to the findings of the presented study, smart factory enablers have the highest weightage among all of the main criteria enablers, followed by strategy and policy enablers. The prioritization of performance metrics reveals that the top three most important performance metrics for RMS are lead time, reconfiguration time, and product flexibility. The feasibility and appropriateness of the framework was tested through a case analysis in the manufacturing organization. The framework developed has a high capacity to assist designers during the adoption of the RMS and will facilitate the identification of the relevant parameters. The authors believe that researchers and professionals will find this study as a ready reference for the stepwise adoption of RMS. The study presented here is likely the first to present a hybrid framework for RMS in which a set of enablers and performance metrics are presented together. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) is a promising manufacturing technology; it has great manufacturing capabilities and large material diversity, making it applicable for many applications. However, the limited information related to AM processes, materials, and rules restricts its potential popularity over traditional manufacturing methods. For a particular application, the choice of available AM process/machine and material is critical to the application's quality, mechanical properties, and other important factors. Moreover, the large number of AM processes/machines and materials and the overlap among them in terms of capability and functionality further complicate the selection task. AM service selection as a problem has three essential aspects, and all support systems that are built to help users select the optimal AM service must consider these aspects during the system development stage. These aspects are the AM resource capability information source, user intervention, and the methodology suggesting the best AM resources that meet user requirements. These aspects actually represent AM resource definition accuracy and availability, selection system usability, and reliability. This study analyses the essence of these three aspects, reviews the literature, and develops a new AM selection system framework that enhances system functionality regarding these aspects. First, 3D printing service providers in the proposed system are considered the source of AM resource capability information to expand AM service options to users, provide accurate resource definitions, and ensure their availability. Second, the proposed system applied the posteriori-based multicriteria decision-making approach through the integration of decision making trial and evaluation laboratory (DEMATEL), analytic hierarchy process (AHP), and modified Technique for Order Preference by Similarities to Ideal Solution (TOPSIS) techniques. This greatly minimizes user inputs during AM service selection process, fully supports the DFAM (Design for additive manufacturing) concept, and maintains the accuracy of final selection decisions. [ABSTRACT FROM AUTHOR]

In order to study the correlation between parameters and performance indicators in the cutting process, the importance of different parameters in performance indicators should be determined. In the present study, the side milling process of titanium alloy by the end milling cutter is considered the research object, and analytic hierarchy process and grey-fuzzy evaluation method are used to evaluate the importance of tool geometric parameters and operating parameters on tool wear rate and material removal rate obtained by FEM method. It is found that applying the average method to remove the parameter level makes each parameter achieve the same result. Therefore, this method should be combined with other data processing methods to resolve the above problem. Finally, the range analysis method is applied to obtain the optimal parameter level of different parameters for each performance indicator. The obtained results show that the helix angle has the highest overall importance value, followed by feed per tooth. And the optimum combination of parameters for tool wear rate and material removal rate is obtained respectively. [ABSTRACT FROM AUTHOR]

Existing ubiquitous manufacturing (UM) systems usually plan production and logistics simultaneously to enhance efficiency. A UM system can be further benefited by pursuing economical fabrication, improving product quality, and enhancing partner relationships, which involves possibly conflicting goals, but has rarely been investigated. To address this, an evolving fuzzy approach is proposed in this study by hybridizing diversifying fuzzy analytic hierarchy process (DFAHP), genetic algorithm (GA), and fuzzy technique for order preference by similarity to the ideal solution (FTOPSIS). The evolving fuzzy approach has been applied to a UM system. The superiority of the evolving fuzzy approach over existing methods in meeting various goals was successfully demonstrated by the experimental results. [ABSTRACT FROM AUTHOR]

Proper selection of cooling/lubricating technique is very important in the machining of difficult-to-cut materials such as nickel-based alloys due to their poor machinability. Among the available cooling/lubricating techniques, high-pressure jet-assisted machining offer remarkable opportunities in terms of increasing the productivity, reducing temperature in the cutting zone, excellent chip-breaking ability, and reduction of the costs associated with cooling/lubrication fluids. This article presents experimental investigation and multi-objective optimization of machining parameters of the high-pressure jet-assisted turning of Inconel 718 with coated carbide tools. The Taguchi L27 orthogonal array was used for the experimental design. Diameter of the nozzle, distance between the impact point of the jet and the cutting edge, pressure of the jet, cutting speed, and feed were considered as machining parameters. In order to optimize the six performance characteristics, namely cutting power, hydraulic power, material removal rate, surface roughness, cutting tool temperature, and chip length, Taguchi-based grey relational analysis and genetic algorithms were applied as multi-objective optimization approaches to identify the optimal levels of machining parameters. Moreover, the weights of the responses were determined by employing the analytic hierarchy process. Finally, a confirmation experiment with the machining parameters in their optimal levels was conducted with the aim to demonstrate the effectiveness of proposed multi-objective optimization approaches. [ABSTRACT FROM AUTHOR]

The application of three-dimensional (3D) printing can enhance not only the competitiveness but also the sustainability of an aircraft manufacturing or maintenance, repair, and overhaul (MRO) company. This study sought to identify the critical factors for such applications. Herein, first, the long-term opportunities and challenges facing an aircraft manufacturing or MRO company planning to apply 3D printing technologies are discussed. The critical factors for enhancing their sustainability are identified from the discussion results. The priorities of critical factors are usually ranked using the fuzzy analytic hierarchy process (FAHP). However, existing FAHP methods cannot rank priorities reasonably when experts (or decision-makers) fail to reach an overall consensus. To address this problem, a novel partial consensus (PC)-FAHP approach is proposed that seeks to obtain a partial consensus among experts. After assessing the effectiveness of the proposed methodology with a case study involving three experts, the most critical factors were identified to be the long-term cost-effectiveness, number or types of aircraft parts that are or will be 3D printable, and advances in research and development that have been made already or are expected in the near future. In addition, the ranking result obtained using the PC-FAHP approach was different from that obtained using existing FAHP methods. [ABSTRACT FROM AUTHOR]

During the part design process, the main objective is usually the maximum performance in use. For aircraft structural parts, the best ratio between mechanical resistance and weight is sought. However, these objectives can lead to geometries which are complex to manufacture. The DFM method presented here is based on concepts from morphological studies and analytic hierarchy process (AHP) to optimize the geometry of an I-Beam considering its manufacturing process and use. To do this, all the I-Beam alternatives that fit into the mechanical environment of the part are listed. Performance indicators are then defined to evaluate the weight, mechanical resistance, and manufacturability of each I-Beam. Then, performance indicators are compared and their relative priority measured on a ratio scale. Finally, the various I-Beam alternatives are compared using a macro-indicator composed of all the performance indicators in order to find the best geometry for the part considering its industrial and economic environment. [ABSTRACT FROM AUTHOR]

Automobile development is a complex system engineering with multi-objective coupling. Setting an accurate mass target to ensure the vehicle performance is the chief work of the vehicle mass development. This article analyzes key characteristic parameters which relate to vehicle mass from the aspect of customer needs and mapping relation between key characteristic parameters and vehicle mass through statistical analysis based on the vehicle mass data of benchmark cars. To meet the requirement of different development indexes and to ensure the vehicle performance, the impact of each characteristic parameter on the mass target is determined through analytic hierarchy process (AHP) and quality function deployment (QFD) methods. Finally, this article develops mass target setting model and puts forward a new method and application steps of setting vehicle mass target. Through practical usage, the new method can ensure the vehicle performance, and increase the accuracy and reliability of mass target. Besides, the method makes the vehicle mass development more knowledgeable and agile. [ABSTRACT FROM AUTHOR]

The business performance of manufacturing organizations depends on the reliability and productivity of equipment, machineries and entire manufacturing system. Therefore, the main role of maintenance and production managers is to keep manufacturing system always up by adopting most appropriate maintenance methods. There are alternative maintenance techniques for each machine, the selection of which depend on multiple factors. The contemporary approaches to maintenance technique selection emphasize on operational needs and economic factors only. As the reliability of production systems is the strategic intent of manufacturing organizations, maintenance technique selection must consider strategic factors of the concerned organization along with operational and economic criteria. The main aim of this research is to develop a method for selecting the most appropriate maintenance technique for manufacturing industry with the consideration of strategic, planning and operational criteria through involvement of relevant stakeholders. The proposed method combines quality function deployment (QFD), the analytic hierarchy process (AHP) and the benefit of doubt (BoD) approach. QFD links strategic intents of the organizations with the planning and operational needs, the AHP helps in prioritizing the criteria for selection and ranking the alternative maintenance techniques, and the BoD approach facilitates analysing robustness of the method through sensitivity analysis through setting the realistic limits for decision making. The proposed method has been applied to maintenance technique selection problems of three productive systems of a gear manufacturing organization in India to demonstrate its effectiveness. [ABSTRACT FROM AUTHOR]

This study investigated the effects of surface texture in a compressor impeller shaft on its remanufacturing using high-velocity oxy-fuel (HVOF). Nine main types of surface texture were prepared. The HVOF system was used to remanufacture samples related to the appearance of these surface texture features, and the samples without texture were selected as the control group. The performance of remanufactured samples was evaluated by the scratch method. The effect of the surface texture factor level on first cracks that occurred (critical load L) was investigated using the analytic hierarchy process (AHP) method. The levels of various factors that influence the indicator weight, as well as the preferred combination, were determined. The representative cross-sectional morphologies and element distribution of the preferred coated samples were investigated using scanning electron microscopy (SEM) and elemental line scanning, respectively. Results indicate that the coating combined with the substrate mainly through a mechanical method, and adhesion strength was substantially improved via a suitable surface texture. It can be concluded that fabricating a suitable surface texture is an effective way to improve the coating adhesion strength of the shaft remanufactured using HVOF. [ABSTRACT FROM AUTHOR]

In the design of automotive components, substitution of metal with natural fibre as base material is commonly found due to high-energy consumption in producing metal components that affects the environment. Therefore, in this study, natural fibres were selected for a hybrid bio-composite material in the design for an automotive anti-roll bar in order to determine the suitable natural fibre that could satisfy the requirements both of customers and the environment. The study was performed using a combination of Analytic Hierarchy Process and Quality Function Deployment for Environment. In making the final decision, life cycle assessment was performed to support the environmental requirements. The results show that sugar palm fibre is the fibre that can best satisfy the design requirements, with 21.51 % of the total score, followed by kenaf, which obtained 20.18 %. Lastly, both the fibres were compared for the life cycle assessment and the results show that sugar palm has a 10 % lower impact on the environment due to its lower energy consumption and CO footprint. Hence, sugar palm fibre is selected as the material to use in the hybrid bio-composite for the automotive anti-roll bar. [ABSTRACT FROM AUTHOR]

To address the problem of how to build quantitative evaluation index models that reflect the essential characteristics of reconfigurable manufacturing system (RMS) and rank alternative reconfiguration schemes, which possess both advantages and disadvantages, an evaluation method based on the preference ranking organization method for enrichment evaluation (PROMETHEE) is proposed. Based on a consideration of the reconfiguration of the reconfigurable machine components and manufacturing cells, quantitative models of the key characteristics of an RMS (scalability, convertibility, diagnosability, modularity, integrability, and customization) are established, after which the quantitative models are used as the basis for constructing an RMS evaluation index system. The analytic hierarchy process (AHP) is used to assign the weights for these indices. During the evaluation process, PROMETHEE I is first applied to analyze the advantages and disadvantages of each alternative scheme. Then, PROMETHEE II is adopted to analyze the net advantages of the schemes. Finally, all of the alternative configurations are ranked according to the analysis results above. The workshop of an institute that has both research and production capabilities was used as an example to validate the effectiveness and practicability of the proposed method. The example contains 10 alternative reconfiguration schemes, and each scheme consists of six evaluation indices. The computation result shows that quantitative models of six key RMS characteristics are equipped with the ability of quantitative description of the RMS reconfiguration scheme, which gives intuitive decision-making information combined with PROMETHEE, including advantage and disadvantage between alternative schemes, for a decision-maker to select the satisfactory configuration. In addition, only a 7.2 % data loss during the evaluation data processing means the rationality of the selected evaluation index and evaluation algorithm. [ABSTRACT FROM AUTHOR]

In this study, a case library for body-in-white (BIW) fixtures is constructed based on the structure of fixtures. The analytic hierarchy process (AHP) is applied to differentiate the factors influencing fixture cases. Weight calculations and the distribution of the weight coefficient of case properties are presented by adopting a 1-to-9 scaling algorithm. Furthermore, the similarity between cases is calculated using the nearest-neighbor approach. The parameterization of a fixture case is demonstrated in an example of a pneumatic fixture with two links. The rules for the revision of case parameters and the assembly positioning of case are given. A prototype case-based reasoning system for a fixture library is developed in C++ for NX software. Finally, a design case study is used to present the applicability and usability of the proposed reasoning system. [ABSTRACT FROM AUTHOR]

Selection of an appropriate sustainability strategy is a multi-criteria decision making (MCDM) problem for manufacturing organizations due to incommensurate and conflicting evaluation criteria. In addition, incomplete information and different opinions of decision makers lead to uncertainties such as interval data and fuzziness. This study proposes a hierarchal MCDM method by combining Analytical Hierarchal Process (AHP) and VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) methods under interval-valued fuzzy environment to deal with ranking of sustainable manufacturing strategies. Linguistic variables were used to assess the ratings of strategies and weights for selection criteria. These linguistic variables were expressed in the triangular interval-valued fuzzy sets. Using a case study of manufacturing small and medium enterprise, the final ranking of the strategies was elicited in accordance with this procedure. Subsequently, a sensitivity analysis was performed to validate the stability of the proposed final ranking. This method can be used as a decision making tool for alternative or strategy selection in other areas where uncertainties are inherent. [ABSTRACT FROM AUTHOR]

Assembly sequence planning is one of the well-known combinatorial optimization problems in manufacturing. An assembly is often represented as an assembly relation graph or precedence graph. The traditional methods are used to generate a large number of feasible assembly sequences and then find the optimal sequence through evaluation. A lot of computation resources are needed. To reduce the complexity of assembly sequence planning, the assembly is converted into a weighted assembly precedence graph considering multiple assembly constraints, i.e., the qualitative and quantitative constraints. The vertices in the weighted precedence graph are the parts or components. The qualitative constraints including the topological and geometrical assembly constraints guarantee to derive the feasible assembly sequences. Some process constraints are also taken as the qualitative constraints. They are represented as the directed edges in the weighted assembly precedence graph. The other assembly constraints, such as the stable support, connector strength, changes of assembly directions, and tools and so forth, are quantified as indices to compute the cost of assembly relations with the fuzzy analytical hierarchy process. The costs are taken as the heuristic information to find the optimal or near-optimal assembly sequences. With the weighted assembly precedence graph, the search space of the optimal assembly sequence will be reduced. We design a minimum spanning tree-based algorithm to detect the optimal assembly sequence based on the weighted assembly precedence graph. The optimal assembly sequences are found in O( n) computation time, where n is the number of the discrete parts. [ABSTRACT FROM AUTHOR]

A combined two-staged analytical hierarchy process (AHP) was proposed with respect to its compatibility in selection of e-textile architecture. Specifically, it was examined in its ability to support decision in determination of appropriate e-textile structures prior to sensor integration. The e-textile structure selection methodology for sensor integration was implemented by interviewing with the experts from the fields of textiles and electronics; hence, it was constructed as two-staged methodology including both experimental study and AHP. In this respect, different e-textile structures including transmission lines containing 15 different conductive yarn types with three different weave types were manufactured via weaving technology in the first stage as experimental part of the methodology, and then, in the second stage, the alternatives based on experimental study were evaluated using AHP. The comparisons were made using priority scales assigned by expert team and synthesized to get aggregated global ratings. In conclusion, appropriate e-textile structures based on weaving manufacturing technology for sensor integration were chosen using AHP technique by ranking alternatives. [ABSTRACT FROM AUTHOR]

Aiming at the shortcomings of manufacturing enterprises, cloud manufacturing (CMfg), as a new type of service-oriented manufacturing mode, is put forward recently. Due to the rapid development of information and other high-tech technologies, CMfg excellently satisfies the development requirements of modern manufacturing and gains some popularity. As one of the key characteristic for CMfg system, the management, sharing, and scheduling of resources and tasks will directly affect the accuracy and efficiency of CMfg service platform. In order to achieve the effective management, convenient use, and reliable transactions of resources and tasks, a framework of trust evaluation system in CMfg is established and a trust evaluation model of CMfg service platform oriented to mechanical manufacturing field is proposed. In this system, the weights of six trust evaluation indexes are obtained through analytic hierarchy process (AHP) method. Meanwhile, the quantitative and update algorithm for direct trust service is designed through a discrete method. Furthermore, the recommendation trust service is extracted through cloud theory model and cloud focus evaluation method. Experiments based on virtual transaction data are conducted to verify the validity and efficiency of the proposed trust evaluation model. [ABSTRACT FROM AUTHOR]