A multi-objective framework for the design of vacuum sealed molding process

This paper provides a framework for process design to achieve simultaneous improvement of the multiple features of the product. The methodology provides a way to integrate process parameters with the product features. Many of the features may be conflicting in nature, and thus may limit the use of a particular setting of design parameter of the process to produce the quality product. In this paper we discuss how to resolve the conflicting objectives of the process design problem. A case study for the design of vacuum-sealed molding process using the proposed methodology is included.     

Evidential reasoning-based Fuzzy AHP approach for the evaluation of design alternatives’ environmental performances

With the growing general awareness of the need to protect the environment as well as the increasingly stringent regulatory requirements imposed by various national and cross-national bodies, manufacturers have to minimise the environmental impacts of their products. Environmental considerations have therefore become a new key criterion for evaluating design alternatives during the product development stage. To facilitate non-Life Cycle Assessment (LCA) experts, such as most product designers, in evaluating the design alternatives in terms of environmental friendliness, this paper introduces a decision-making mechanism that combines the multiple criteria decision making (MCDM) approaches with LCA methodology. This evidential reasoning-based approach is a fast-track and objective tool which ranks the available design alternatives according to their potential environmental impacts. The environmental impacts of design alternatives assessed by the LCA are used for the weight elicitation processes of the proposed approach. A case application is conducted to illustrate the use of the proposed method to evaluate the environmental performances of design alternatives.     

Structural optimization strategies to design green products

This paper addresses the need for a structured approach to environmental assessment and improvement. We propose a computer-aided methodology, named Eco-OptiCAD, based on the integration of Structural Optimization and Life Cycle Assessment (LCA) tools. Eco-OptiCAD supports the designer during product development, highlighting when and where the core of the environmental impact lies. Furthermore, it provides effective tools to address such impacts, improving the original product, while ensuring structural and functional requirements. It foresees the synergic use of (1) virtual prototyping tools, such as 3D CAD, Finite Element Analysis (FEA) and Structural optimization, (2) function modeling methodology and (3) Life Cycle Assessment (LCA) tools. The kernel of the methodology is constituted by a set of optimization strategies and a module, named Life Cycle Mapping (LCM). In particular, we have conceived ten optimization strategies converting environmental objectives and constraints into structural and geometrical parameters. They enable the designer to generate alternative green scenarios according to the triad shape–material–production. The LCM tool has been specifically developed to easily trace the growth of environmental impacts throughout the product's life cycle and allow the user to focus his effort on the most relevant aspects. Thanks to the integration of the structural optimizer with an LCA map, the designer becomes aware of the consequences that each change in the geometry, the material or the manufacturing process will produce on the environmental impact of the product throughout its life cycle. With a complete view of the product life cycle, the designer can improve a single phase, while retaining a global perspective; thus avoiding the possibility of gaining a local green improvement at the cost of a global increase in environmental impacts.     

Six-Sigma project selection using national quality award criteria and Delphi fuzzy multiple criteria decision-making method

Six-Sigma is a tactical tool of significant value in achieving operational excellence. The project selection decision, under a resources constraint, is the early stage of implementation for a Six-Sigma intervention. The project selection decision is challenging due to its fuzzy group decision-making aspect inherent to the problem. The present study proposes to adopt national quality award criteria as the Six-Sigma project selection criteria, and proposes a hierarchical criteria evaluation process. The strategic criteria are evaluated by the management team using a Delphi fuzzy multiple criteria decision-making method. Then, the tactical sub-criteria which contain additional operational issues are evaluated by the Six-Sigma Champion. The proposed methodology is successfully applied in solving the project selection problem deriving from a component manufacturer. The empirical outcomes are promising. Moreover, the results show that the higher a project’s priority is, the greater the financial gains will be on completion of the project. Accordingly, the proposed methodology can prioritize the financial gain – which is the key performance indicator for a Six-Sigma project. Additionally, the quality status of the case company has been significantly improved through implementation of the Six-Sigma project. The systematic evaluation process also influences employees to adopt an analytical operations philosophy. Moreover, the commercial objectives of the company are brought into focus by the proposed methodology.     

Including the environmental criteria when selecting a wastewater treatment plant

Life Cycle Assessment (LCA) is a methodology to generate environmental impact estimates associated with the life cycle stages of a product or process. The approach facilitates a more comprehensive outlook of the end-of-pipe process impacts, in which wastewater treatment plants (WWTPs) are included. Here we describe the implementation of the LCA methodology within a knowledge-based Decision support system (DSS) in order to include the environmental criteria to the decision making process when selecting the most appropriate process flow diagrams for specific scenarios. A sample group of 22 actual operating facilities in Spain, corresponding to five different typologies were assessed by two relevant impact categories within the system: Eutrophication Potential (EP) and Global Warming Potential (GWP). DSS includes useful tools that support a user in choosing a consistent, near optimum solution for an environmental impact specific problem in a reduced time frame. The synergistic combination of the two methodologies to address the design and assessment of treatment facilities can serve to identify the most sustainable options, embracing simultaneously a wide variety of analysis criteria, and enhancing the calculation of environmental savings. Results of averaged paired-comparison ratios between DSS estimates and facilities operations empirical data showed up to 70% and 95% EP and GWP, respectively. Interestingly, when unbiased operational efficiencies for existing facilities were discarded, the matching ratios increased substantially, up to 99% in both cases. The in-depth analysis of different output data gathered during the conceptual design and simulation of operating facilities using DSS identified the best performing facilities; and was used to improve the environmental performance of WWTPs, even during preliminary design of new facilities. Results demonstrated that combined LCA and DSS implementation is a suitable tool to assess WWTP design during the decision-making process. Following this procedure, a reliable interpretation and discussion of the results can be performed.     

Optimal design of controlled multibody dynamic systems for performance,robustness and tolerancing

The multidisciplinary design approach has gained increasing popularity in recent years due to its ability to deal with conflicting design requirements imposed by discipline-specific objectives. The traditional design process involving multiple disciplines is typically a sequential process where the design objectives are met one at a time in a sequence of designs. However, in doing so, unnecessary limitations are imposed on the design parameters and the final design is far from being optimal. The effectiveness of integrated design methodology has been proven and such designs are being obtained in many applications. However, most of the work in this area has been problem and/or system specific and does not address important manufacturing considerations, such as tolerance allocation, robustness with respect to machining tolerances, etc. The results presented in this paper are intended to contribution towards filling these gaps. In particular, the new approach will help designers avoid a common known pitfall of performance optimization, i.e. the fact that designs that are optimized for performance alone are notoriously sensitive to deviations from the nominal design. Thus, optimizing for performance alone leads to designs that fall below acceptable standards of robustness; they are also expensive to manufacture because the tolerances must be kept very tight to ensure acceptable performance. The approach presented here will allow the user to systematically tradeoff performance versus robustness and tolerancing concerns. A proof-of-concept example that was solved to evaluate this methodology is also presented in this paper. This example provides a convincing demonstration of the fact that small sacrifices in performance can yield huge benefits in the other areas, provided a methodology is available for making these tradeoffs in a systematic way. This especially can be used by designers in various fields such as automotive, aerospace, deployable structures, machine tools (including hexapods), robotic systems, precision machinery, etc.     

An integrated AHP and VIKOR for design concept evaluation based on rough number

Design concept evaluation at the early stage of product design has been widely recognized as one of the most critical phases in new product development as it determines the direction of the downstream design activities. However, the information at this stage is mainly subjective and imprecise which only depends on experts’ judgments. How to handle the vagueness and subjectivity in design concept evaluation becomes a critical issue. This paper presents a systematic evaluation method by integrating rough number based analytic hierarchy process (AHP) and rough number based compromise ranking method (also known as VIKOR) to evaluate design concepts under subjective environment. In this study, rough number is introduced to aggregate individual judgments and preferences and deal with the vagueness in decision-making. A novel AHP based on rough number is presented to determine the weight of each evaluation criterion. Then an improved rough number based VIKOR is proposed to evaluate the design concept alternatives. Sensitivity analysis is conducted to measure the impact of the decision makers’ risk to the final evaluation results. Finally, a practical example is put forward to validate the performance of the proposed method. The result shows that the proposed decision-making method can effectively enhance the objectivity in design concept evaluation under subjective environment.     

Multi-stage multi-objective production planning using linguistic and numeric data-a fuzzy integer programming model

This paper introduces a methodology to solve a multi-stage production planning problem having multiple objectives, which are conflicting, non-commensurable and fuzzy in nature. The production process consists of multiple stages having one or more machines in each stage. Every processing stage produces work-in-process, semi-finished items as an output, which becomes an input to the subsequent stage either fully or partially depending on the cycle times of the machines. Events of machine breakdowns and imbalances in input–output relations in one or more stages may affect both work-in-process (WIP) and final production targets. Our paper provides a methodology based on fuzzy logic to maintain the desired balanced input–output relation at each stage and the targeted production output at the final stage. This is done by procurement of work-in-process inventory (WIP) and installation of new machines at appropriate stages. The objectives or goals expressed in linguistic terms are represented as fuzzy sets. The Induced Ordered Weighted Averaging (IOWA) operator is used to aggregate the objectives as per their priorities and finally to formulate the production process as a Mixed Integer Programming (MIP) problem. The solution to MIP shows the degrees of achievements of the production process objectives. The methodology is illustrated with a real life application of crankshaft productions in an automobile industry.     

Cost-effective design for injection molding

It is commonly agreed that a large proportion of the ultimate product cost is determined at product design stage. Therefore, a cost-effective design cannot be obtained unless all cost issues are resolved at early design stage. Therefore, instead of performing cost estimation after design, research presented in this paper aims to provide on-line cost evaluation and advisory to help product designers avoid cost-ineffective design. The objective can be obtained by (1) identifying factors that might affect product cost at each product design stage, (2) developing a design for cost effectiveness methodology that accommodates the concepts of concurrent engineering, and (3) developing a computer-based design for cost effectiveness system based on the proposed methodology. In this research, we focus on injection molding product design due to the advantages of injection molding process, such as high production rates, excellent quality and accuracy of the parts, and very long mold life. This paper first reviews and characterizes the conventional molding product development process with an emphasis on the identification of cost factors. Based on the results of process characterization, a cost model is developed, which depicts the relationships between cost factors and product development activities, as well as their relationships with product geometry. According to the product life cycle activities and the cost model, a design for cost effectiveness process is proposed. The process and the cost model are then employed for the development of a computer-based product design for cost effectiveness as one of the module of an integrated design for injection molding environment.     

Knowledge management for consumer-focused product design

As the automotive industry adopts a consumer focus in its product development strategy, it offers broader product ranges, shorter model lifetimes and the ability to process orders in arbitrary lot sizes. This offers the ability to conduct early product design and development trade-off analysis among these competing objectives. A distributed knowledge-based system, which analyzes, verifies, stores, and retrieves process definitions, is needed to manage the complexity of workflows. The use of information technologies and networking capabilities is essential in the dissemination of product knowledge in order to integrate the decision-making process among heterogeneous and distributed partners/units. This paper offers insights into a knowledge management approach that enables implementing a consumer-focused product design philosophy by integrating capabilities for intelligent information support and group decision-making utilizing a common enterprise network model and knowledge interface through shared ontologies. An automotive supply chain case study is utilized in illustrating the proposed approach.     

Computer-aided integration of multidisciplinary design information

This paper addresses the integration issues at the preliminary design stage in order to support analysis and decision-making while considering a design from the viewpoint of different disciplines. The paper describes a research project for investigating and designing a framework for intelligent linkage between design drawings and other information system environments, providing access to both external databases and design methods at the preliminary design stage. Accessing such information at this stage will allow designers to carry out the rapid evaluation of design alternatives, analysis and decision-making in a multi-disciplinary, multi-agent design environment. The objectives of the research are outlined, the methodology is discussed and the first application results are demonstrated.     

A two phase multi-attribute decision-making approach for new product introduction

This study aims at improving the quality and effectiveness of decision-making in new product introduction. New product development has long been recognized as one of the corporate core functions to be competitive on an increasingly competitive global market. However, developing new products is a process involving risk and uncertainty. In order to solve this stochastic problem, companies need to evaluate their new product initiatives carefully and make accurate decisions. For this reason, a systematic decision process for selecting more rational new product ideas is proposed. Basically, two stages of decision-making are described: the identification of nondominated new product candidates and the selection of the best new product idea. These stages are composed of an integrated approach based on a fuzzy heuristic multi-attribute utility method and a hierarchical fuzzy TOPSIS method. Finally, an application is given to demonstrate the potential of the methodology.     

Development of a fuzzy decision model for manufacturability evaluation

A manufacturability evaluation decision model is formulated and analyzed based on fuzzy logic and multiple attribute decision-making under the concurrent engineering environment. The study emphasizes on the treatment of the linguistic and vagueness at the early product development stage. The study also considers the function integration of the total life cycle of a product. Hence, the integrated decision model covers the multi-level, multi-goal requirements of the products. Multiple criteria such as the goal space, the decision space, the function space, the development (i.e., product & process design) space, and the activity space, are then applied under different analysis of decision-making methods. For instances, the fuzzy multiple attribute decision-making (FMADM) combined with activity-based costing (ABC) can be used in the activity decision space. The fuzzy logic decision model can be applied in the goal decision space. The results of this study point out the importance of early decision making capability. An example of a high-pressure vessel is provided to demonstrate the proposed model for evaluating the manufacturability.     

Customer-driven product design and evaluation method for collaborative design environments

Product concept generation and evaluation in a product development environment has been identified as the two major activities needed for obtaining an optimal design scheme. Product conceptual design is of critical importance in design through customer involvement for the systematic and simultaneous consideration on the impact of design decisions on manufacturing and assembly leads to repeated and excessive changes in design and processes. This paper introduces a novel knowledge support approach for the organization and ranking of design feature knowledge towards an integrated product model that incorporates a feature-based representation scheme targeted to evaluate the impact of design on subsequent activities in the conceptual design phase, taking into account the presence of design information and user preferences. An uncertain linguistic multi-attribute decision-making evaluation model is proposed and discussed for obtaining an optimal design scheme during the evaluation and selection of product design alternatives in conceptual design. The focus of this paper is on the development of a knowledge-intensive support design scheme and a comprehensive systematic fuzzy evaluation methodology for product conceptual design generation, evaluation, and selection. A case study and the corresponding scenario of knowledge support for design alternatives generation, evaluation and selection are provided for illustration.     

An assembly oriented design framework for product structure engineering and assembly sequence planning

The paper describes a novel framework for an assembly-oriented design (AOD) approach as a new functional product lifecycle management (PLM) strategy, by considering product design and assembly sequence planning phases concurrently. Integration issues of product life cycle into the product development process have received much attention over the last two decades, especially at the detailed design stage. The main objective of the research is to define assembly sequence into preliminary design stages by introducing and applying assembly process knowledge in order to provide an assembly context knowledge to support life-oriented product development process, particularly for product structuring. The proposed framework highlights a novel algorithm based on a mathematical model integrating boundary conditions related to DFA rules, engineering decisions for assembly sequence and the product structure definition. This framework has been implemented in a new system called PEGASUS considered as an AOD module for a PLM system. A case study of applying the framework to a catalytic-converter and diesel particulate filter sub-system, belonging to an exhaust system from an industrial automotive supplier, is introduced to illustrate the efficiency of the proposed AOD methodology.     

Conceptual process planning – an improvement approach using QFD,FMEA, and ABC methods

Conceptual process planning (CPP) is an important technique for assessing the manufacturability and estimating the cost of conceptual design in the early product design stage. This paper presents an approach to develop a quality/cost-based conceptual process planning (QCCPP). This approach aims to determine key process resources with estimation of manufacturing cost, taking into account the risk cost associated to the process plan. It can serve as a useful methodology to support the decision making during the initial planning stage of the product development cycle. Quality function deployment (QFD) method is used to select the process alternatives by incorporating a capability function for process elements called a composite process capability index (CCP). The quality characteristics and the process elements in QFD method have been taken as input to complete process failure mode and effects analysis (FMEA) table. To estimate manufacturing cost, the proposed approach deploys activity-based costing (ABC) method. Then, an extended technique of classical FMEA method is employed to estimate the cost of risks associated to the studied process plan, this technique is called cost-based FMEA. For each resource combination, the output data is gathered in a selection table that helps for detailed process planning in order to improve product quality/cost ratio. A case study is presented to illustrate this approach.     

A structured methodology for implementing engineering data management

One of the most significant positive effects on product and process development in recent years has been the application of data management techniques. Engineering data management or product data management is the most promising one. The implementation of engineering data management is heavily dependent on the engineering process and involves the technologies of management, engineering, and information. However, as there is no commonly acceptable approach and methodologies for implementing engineering data management, it’s implementation becomes a bottleneck.This paper presents a structured methodology for the implementation of engineering data management. The approach consists of a series of steps, from business and engineering process analysis, modeling and reengineering, through system design and modeling, to system realization.This research will facilitate engineering process improvement and the planning, design and implementation of engineering data management. Consequently, it will help increase product development capability and quality, reduce development cycle time and cost, and hence increase product marketability.     

Design for six sigma through robust optimization

The current push in industry is focused on ensuring not only that a product performs as desired but also that the product consistently performs as desired. To ensure consistency in product performance, “quality” is measured, improved, and controlled. Most quality initiatives have originated and been implemented in the product manufacturing stages. More recently, however, it has been observed that much of a product’s performance and quality is determined by early design decisions, by the design choices made early in the product design cycle. Consequently, quality pushes have made their way into the design cycle, and “design for quality” is the primary objective. How is this objective measured and met? The most recent quality philosophy, also originating in a manufacturing setting, is six sigma. The concepts of six sigma quality can be defined in an engineering design context through relation to the concepts of design reliability and robustness – probabilistic design approaches. Within this context, design quality is measured with respect to probability of constraint satisfaction and sensitivity of performance objectives, both of which can be related to a design “sigma level”. In this paper, we define six sigma in an engineering design context and present an implementation of design for six sigma – a robust optimization formulation that incorporates approaches from structural reliability and robust design with the concepts and philosophy of six sigma. This formulation is demonstrated using a complex automotive application: vehicle side impact crash simulation. Results presented illustrate the tradeoff between performance and quality when optimizing for six sigma reliability and robustness.     

Multidisciplinary design optimization of a compact highly loaded fan

The recent progress in Multidisciplinary Design Optimization (MDO) enables engineers to revise design strategies and to address more complex problems. In this paper, the full design of a compact highly loaded fan for aerospace applications is considered. The design comprises several conflicting objectives, such as aerodynamic efficiency and structural integrity. Optimization techniques are applied at every stage of the design, leading to a reduced and accelerated overall process and an enlarged design space. Performance of the machine are first evaluated by through-flow modeling (low-fidelity radial distributions based on experimental correlations) to determine an optimal flow path configuration. High-fidelity aero-mechanical performances are then considered to generate the detailed design of the rotors, including section profiles along the span, as well as lean and sweep. The multi-objective algorithm enables one to consider simultaneously Computational Fluid Dynamics (CFD) and Computational Structural Mechanics (CSM). The methodology is applied to the design of a compact highly loaded fan achieving a 2.1 pressure ratio with an efficiency of 88 % while satisfying the mechanical constraint of titanium with a safety margin of 32 %. The proposed approach allows to generate an original configuration with a reduced time to market.     

An approach to multicriteria fuzzy optimization of a prestressed concrete bridge system considering cost and aesthetic feeling

In practical structural design problems, the designer should take into account several objectives, such as economics, safety, serviceability, aesthetic feeling and so on, and relative evaluations among these different characteristic objectives have some tolerances or fuzziness. For these reasons, the practical optimum structural design process concerning multiobjectives can be defined as a kind of compromising optimum decision-making process with fuzziness. In this paper, a rational, systematic and efficient fuzzy optimum design method for structural systems is developed by combining a suboptimization concept and fuzzy decisionmaking techniques at the discrete combinations of common design variables. The design method is applied to an optimum design problem of a large scale prestressed concrete bridge system considering two objectives; the total construction cost and aesthetic feeling. The rationality, the systematic design process and the efficiency of the proposed method are demonstrated.