Design for manufacturing: application of collaborative multidisciplinary decision-making methodology

Design for manufacturing is often difficult for mechanical parts, since significant manufacturing knowledge is required to adjust part designs for manufacturability. The traditional trial-and-error approach usually leads to expensive iterations and compromises the quality of the final design. The authors believe the appropriate way to handle product design for manufacturing problems is not to formulate a large design problem that exhaustively incorporates design and manufacturing issues, but to separate the design and manufacturing activities and provide support for collaboration between engineering teams. In this article, the Collaborative Multidisciplinary Decision-making Methodology is used to solve a product design and manufacturing problem. First, the compromise Decision Support Problem is used as a mathematical model of each engineering teams’ design decisions and as a medium for information exchange. Second, game-theoretic principles are employed to resolve couplings or interactions between the teams’ decisions. Third, design-capability indices are used to maintain design freedom at the early stages of product realization in order to accommodate unexpected downstream design changes. A plastic robot-arm design and manufacturing scenario is presented to demonstrate the application of this methodology and its effectiveness for solving a complex design for manufacturing problem in a streamlined manner, with minimal expensive iterations.     

Design for life-cycle profit with simultaneous consideration of initial manufacturing and end-of-life remanufacturing

Remanufacturing is emerging as a promising solution for achieving green, profitable businesses. This article considers a manufacturer that produces new products and also remanufactured versions of the new products that become available at the end of their life cycle. For such a manufacturer, design decisions at the initial design stage determine both the current profit from manufacturing and future profit from remanufacturing. To maximize the total profit, design decisions must carefully consider both ends of product life cycle, i.e. manufacturing and end-of-life stages. This article proposes a decision-support model for the life-cycle design using mixed-integer nonlinear programming. With an aim to maximize the total life-cycle profit, the proposed model searches for an (at least locally) optimal product design (i.e. design specifications and the selling price) for the new and remanufactured products. It optimizes both the initial design and design upgrades at the end-of-life stage and also provides corresponding production strategies, including production quantities and take-back rate. The model is extended to a multi-objective model that maximizes both economic profit and environmental-impact saving. To illustrate, the developed model is demonstrated with an example of a desktop computer.     

Distributed product and facility prototyping in extended manufacturing enterprises

In order to reduce the cost at the early product development stages, the planners need methodologies and tools that would allow them to judge upon the implications of the product design on the required manufacturing processes and facilities for their production. This paper reports on a new theoretical platform and a pilot implementation of a decision-making environment for distributed product and facility prototyping in an extended enterprise. The approach is based on an exchange of requests and information between collaborative autonomous agents that support the design, manufacturing planning and facility formation activities. The decision-making is formalized as iterative matching of design, process and facility attributes using multilevel resource capability representation within the extended enterprise. The system is implemented as an XML/CORBA-based environment for conveying design and manufacture messages across traditional technology boundaries. The reported research aims to provide the designers with a rapid manufacturing feasibility assessment tool to be used at different design and planning stages in extended manufacturing enterprises.     

Function-technology-based product platform formation

Product platforms have been effectively used by many successful companies for product family design. Technological advancements and changes in customer needs pose problems for robustly designing product platforms over a given planning horizon. To date, most product platform formation approaches are directed by structural (subassemblies and components) considerations and are seldom undertaken at the conceptual design stage. We argue that product platform design should commence at the conceptual design stage rather than the detailed design stage. It is noteworthy that physical structures are the end results of designs already frozen at higher level of functional abstraction. Hence, tackling the platform formation problem should start much before structures are materialized. We propose that the product platform formation approach should be considered at two different stages: (i) conceptual design stage; and (ii) detailed design stage. In reference to the Function?–?Behavior?–?Structure model proposed by Gero and Kannengiesser (Gero, J.S. and Kannengiesser, U., Function-behavior-structure: A model for social situated agents. Workshop on Cognitive Modeling of Agents and Multi-Agent Interactions, International Joint Conference on Artificial Intelligence 2003, Acapulco, Mexico, 2003, pp. 101–107), conceptual design would refer to the design of products at function and technology stage, whereas detailed design would refer to the design of products at the structure stage. This paper discusses a method to form product platforms at the Function-Technology stage which can be correspondingly mapped to the structural stages. Thus, forming product platforms at a higher level of abstraction would enable a better understanding of the complications met at structural level. The FT approach uses Function Technology Ant Colony Optimization (FTACO) method to determine product platform configuration(s). We demonstrate the proposed approach using the example of a computer mouse product family.     

Product service systems,after-sales service and new product development

After-sales service is a critical element in the successful marketing of many products. Capital goods, for example, manufacturing equipment, require after-sales service such as maintenance and repair in order for customers to get the full value from them. Some manufacturers have started to offer customers an integrated product and service, termed a product-service system in the academic literature. However, in order to deliver such integrated offerings, a different approach to new product development (NPD) is required. This is because the product design influences after-sales service requirements, and so this needs to be considered during NPD. However, researchers have largely ignored the relationship between NPD and service. To address this gap, six in-depth case studies were conducted at leading companies that offer a combined product-service offering, to identify how service requirements are typically evaluated at the design stage. The results show that at companies where after-sales is an important element of the business, service requirements are systematically evaluated during NPD through the involvement of after-sales personnel and the use of field service data to set design goals.     

Towards a generic product modelling framework

In response to the current rapidly changing manufacturing environment, product modelling technology has been widely applied to provide the essential information for product development (PD) processes. The traditional product modelling technologies are unable to support the information exchange and share in various stages of PD processes that could be taken place among departments in a company or even among companies in distributed manufacturing environment. This has caused many problems such as information loss, data format incompatibility and reduced efficiency and effectiveness of product data applications. This has consequently created bottlenecks for the integration of PD processes. In this paper, a generic product modelling framework (GPMF) is proposed to overcome the abovementioned problems in today's manufacturing environment. This framework uses the standard for the exchange product model data (STEP) as a foundation. It consists of four functional components: an EXPRESS data model namely EDM; a STEP–based modelling environment; a “five-phase” modelling method; and three EDM data exchange and sharing methods. Case studies show that the product models built based on the GPMF are capable of integrating information in product design, manufacturing and assembly. The GPMF is compatible, comprehensive, and flexible, and is able to support information exchange and sharing.     

Evaluation of Product and Process Design Robustness

Critical design decisions are commonly made throughout the product development process assuming known material and process behavior. However, stochastic variation during manufacture can inadvertently result in inferior or unacceptable product performance and reduced production yields. Stochastic simulations have been developed to estimate the end-use performance distribution prior to the commitment of hard tooling. This article proposes a definition for integrated product and process robustness, and extends existing stochastic methods to model the important role of the manufacturing flexibility in elimination of defects and product optimization. The goal is to enable the designer to understand and account for not only the negative effects of manufacturing variation, but also the positive impact of manufacturing flexibility wherein instantaneous corrections in the manufacturing process can frequently improve the product quality and eliminate flaws in the product design. Then, a methodology is introduced and contrasted with conventional development methods in the evaluation of best practices for development of a molded plastic component.     

A novel approach to include sustainability concepts in classical DFMA methodology for sheet metal enclosure devices

Nowadays sustainable design is a mandatory requirement in the product development process. For this reason, design methodologies are addressed to establish a close relationship between environmental, social and economic impact indicators and product features from early design stages, especially in those features related to its manufacturing. In this paper, the design for manufacturing and assembly—DFMA methodology is adapted to sheet metal enclosure devices, integrating functional and component relationships to minimize particular sustainability indicators such as energy consumption, carbon footprint, number of parts, required amount of material, assembly time and manufacturing costs. Savings with the proposed method are achieved following specific sub-tasks oriented to define new simplified product components, considering changes in manufacturing processes and re-defining mechanical connections between parts. Traditional DFMA approaches consider manufacturing and assembly issues related to a reduction of product complexity and economic savings. The proposed method aims to examine the benefits in life cycle stages such as raw material consumption, service, maintenance, upgrading and end of life—EOL. The methodology is validated through a redesign of a sheet metal industrial clock, in which the sustainability impacts are calculated from a comparison of an existent product vs. a new product development. The implementation of the method in the case study demonstrate reductions of more than 25% in product mass, consumed energy and CO₂ footprint, and more than 50% in theoretical assembly time and product complexity. Sustainability indicators of the proposed method are selected from literature analysis and taking into account attributes of sheet metal enclosure devices.     

An intelligent physarum solver for supply chain network design under profit maximization and oligopolistic competition

We propose an efficient bio-inspired algorithm for design of optimal supply chain networks in a competitive oligopoly markets. The firms compete in manufacture, storage and distribution of a product to several markets. Each firm aims at maximisation of its own profit by optimising the design capacity and product flow in the supply chain. We model the supply chain network as a multi-layer graph of manufacturing nodes, distribution nodes and storage centres. To optimise the network, we adopt the mechanisms of a foraging behaviour of slime mould Physarum polycephalym. First, we extend the original Physarum model to deal with networks with multiple sources and sinks. Second, we develop a novel method to solve the user equilibrium (UE) problem by exploiting the adaptivity of the Physarum model: we update the link costs according to the product flow. Third, we refer to an equivalent transformation between system optimum problem and UE problem to determine the optimal product flows and design capacities of a supply chain. At last, we present an approach to update the amount of product supplied by each firm. By comparing our solutions with that in Nagurney (2010b) on several numerical examples, we demonstrate the efficiency and practicality of the proposed method.     

Novel method to construct large-scale design space in lubrication process utilizing Bayesian estimation based on a small-scale design-of-experiment and small sets of large-scale manufacturing data

A large-scale design space was constructed using a Bayesian estimation method with a small-scale design of experiments (DoE) and small sets of large-scale manufacturing data without enforcing a large-scale DoE. The small-scale DoE was conducted using various Froude numbers (X₁) and blending times (X₂) in the lubricant blending process for theophylline tablets. The response surfaces, design space, and their reliability of the compression rate of the powder mixture (Y₁), tablet hardness (Y₂), and dissolution rate (Y₃) on a small scale were calculated using multivariate spline interpolation, a bootstrap resampling technique, and self-organizing map clustering. The constant Froude number was applied as a scale-up rule. Three experiments under an optimal condition and two experiments under other conditions were performed on a large scale. The response surfaces on the small scale were corrected to those on a large scale by Bayesian estimation using the large-scale results. Large-scale experiments under three additional sets of conditions showed that the corrected design space was more reliable than that on the small scale, even if there was some discrepancy in the pharmaceutical quality between the manufacturing scales. This approach is useful for setting up a design space in pharmaceutical development when a DoE cannot be performed at a commercial large manufacturing scale.     

Fuzzy adaptive preventive maintenance in a manufacturing control system: a step towards self-maintenance

In this paper, a framework of integrating preventive maintenance (PM) and manufacturing control system is proposed. Fuzzy-logic control is used to enable an intelligent approach of integrating PM and a manufacturing control system. This will contribute to the novel development of an integrated and intelligent framework in those two fields that are sometimes difficult to achieve. This idea is based on combining work on an intelligent real-time controller for a failure-prone manufacturing system using a fuzzy-logic approach (Yuniarto, M.N. and Labib, A.W., Optimal control system of an unreliable machine using fuzzy logic control: from design to implementation. Int. J. Prod. Res. (in press a); Yuniarto, M.N. and Labib, A.W., Intelligent real time control of disturbances in manufacturing systems. Integr. Manuf. Syst.: Int. J. Manuf. Technol. Manage. (in press b) and the work on PM proposed by Labib et al. (Labib, A.W., Williams, G.B. and O’Connor, R.F., An intelligent maintenance model (system): an application of analytic hierarchy process and a fuzzy logic rule-based controller. J. Oper. Res. Soc., 1998, 49, 745–757)). The aim of the research is to control a failure-prone manufacturing system and at the same time propose which PM method is applicable to a specific failure-prone manufacturing system. The mean time to repair and mean time between failures of the system are used as integrator agents, by using them to couple the two areas to be integrated (i.e. a maintenance system and manufacturing system).     

Optimal process parameter determination for computer‐aided manufacturing

Producing high‐quality products at low cost is one of the key factors to survival for manufacturing sectors in today's intense global competition environment. One way to gain competitiveness is to integrate product design and process planning into one activity. This study attempts to determine optimal process parameters for a manufacturing process under given design parameters. The process parameters to be determined in this study include process means and process tolerances for particular manufacturing process sequences. The problem is formulated in constrained non‐linear optimization, considering both quality‐ and manufacturing‐related costs. The proposed application evaluates alternative product designs and process sequences so that the best associated process parameters can be determined during the early stages of design and planning. This makes the link between CAD and CAM systems more useful and effective. As a result, optimal integration of product design and process planning with minimal production costs and maximal product quality is possible. Copyright © 1999 John Wiley & Sons, Ltd.     

Information sharing in multiviewpoint injection moulding design and manufacturing

Global competitiveness challenges manufacturing industry to bring to market well designed and manufactured new products at competitive prices in as short a lead-time as possible. To achieve this, inputs are needed from experts in a multitude of disciplines as well as from customers and suppliers. While the use of design teams is achieving success, there is a need for modern software tools that support design and manufacture to be radically improved. Typically, design for manufacture software systems does not support the multiple views of information needed for information systems to be able to support multiple manufacturing perspectives. This paper proposes a linked, multiviewpoint, product model structure as a means of supporting the many views of product information necessary in team-based design and manufacturing systems. To test the ideas developed, an experimental product model has been implemented using an object-oriented database that focuses on views related to the design and manufacture of injection-moulded products. The experimental system explores the relationships between three views: mouldability, cavity design and cavity machining views.     

Flexible fixture design and automation: Review,issues and future directions

The cost of designing and fabricating fixtures can amount to 10-20% of the total manufacturing system costs. To reduce manufacturing costs, a fixture system is designed to be competent in fixturing as many workpieces as possible. In mass volume production, this can be achieved by fixturing a large quantity of the same kind of workpieces. In low-to-medium volume production, however, improvement of the flexibility of fixture systems becomes a favourable way to reduce the unit cost of product. This paper summarizes the latest studies in the field of flexible fixture design and automation. First, a brief introduction is given on this research area. Secondly, taxonomy of flexible fixture design activities is presented. Thirdly, the flexibility strategies based on the existing flexible fixture systems are discussed. Fourthly, the contributions on design methodologies and verifications are examined. Fifthly, advances on computer-aided design and see-up systems are summarized. Finally, some prospective research trends are presented.     

Preventive maintenance of manufacturing systems under environmental constraints

The paper describes a new preventive maintenance approach for manufacturing systems under environment constraints. The manufacturing system under consideration consists of a machine M₁ that produces a single product in a Just-in-Time context. To satisfy a constant demand d, the system called upon another machine M₂ (the subcontractor), comprising the so-called environment, which produces at a certain rate the same type of product as M₁. Both machines are subjected to random failures. Whereas machine M₂ is uncontrollable from the maintenance point of view, an age-limit policy is used for preventive maintenance of machine M₁. It is proved that the best age to perform preventive maintenance depends on the history of machine M₁ and the state of M₂. A numerical example is used to illustrate the proposed approach.     

Development of a high-throughput UHPLC–MS-based content uniformity method as a tool for assessing dry powder inhalers

Background: Dry powder inhaler (DPI) product manufacturing requires the assessment of uniformity at various stages of the manufacturing process. Results: To efficiently and precisely determine the uniformity of the small doses inherent to DPI technology, an ultrahigh-performance liquid chromatography–mass spectrometry (UHPLC–MS)-based content uniformity method was developed. Using mathematical modeling and proper selection of bracketing standards, a volumetric approximation of sample weight was utilized, eliminating the need for accurate sample weights and reducing sample preparation time. Conclusion: UHPLC–MS coupled with mathematical modeling makes high-throughput CU testing of DPI drug products possible which allows for an enhanced understanding of the manufacturing process.     

Concurrent optimization of assembly tolerances for quality with position control using scatter search approach

Tolerance allocation to individual parts in any assembly should be a vital design function with which both the design and manufacturing engineers are concerned. Generally design engineers prefer to have tighter tolerances to ensure the quality of their design, whereas manufacturing engineers prefer loose tolerances for ease of production and the need to be economical. This paper introduces a concurrent tolerance approach, which determines optimal product tolerances and minimizes combined manufacturing and quality related costs in the early stages of design. A non-linear multivariable optimization model is formulated here for assembly. A combinatorial optimization problem by treating cost minimization as the objective function and stack-up conditions as the constraints are solved using scatter search algorithm. In order to further explore the influence of geometric tolerances in quality as well as in the manufacturing cost, position control is included in the model. The results show how position control enhances quality and reduces cost.     

Optimal production plan for a multi-products manufacturing system with production rate dependent failure rate

This study deals with the problem of dependence between production and failure rates in the context of a multi-product manufacturing system. It provides an answer about how to produce (i.e. the production rates) and what to produce (i.e. which product) over a finite horizon of H periods of equal length. We consider a single randomly failing and repairable manufacturing system producing two products P_a and P_b . The product P_a is produced to supply the strategic demand d(k) of the principal customer via a buffer stock S over k periods (k?=?1,?2,?…?,?H). The second product P_b is produced to meet a secondary but very profitable demand. It is produced during a given interval at the end of each period k. We develop a genetic algorithm to determine simultaneously the optimal production rate of the first product during each period k and the optimal duration of the production interval of the second product, maximising the total expected profit.     

An object-oriented modeling framework for representing uncertainty in early variant design

This article presents a framework for the representation of uncertainty in the early design of complex adaptive products such as automobiles. The core of the framework is an object-oriented approach in which design objects and their inter-relationships may be modeled, and in which both the design attributes and the product structure may be uncertain. Relationship objects allow product variants and design alternatives to be represented. In addition to the design model, derivation methods for design attributes may be modeled, and methods may be incorporated to allow the deterministic or probabilistic computation of attributes. The modeling framework is the basis of a risk modeling tool, RiTo, in which Monte Carlo simulation is used to compute estimates for costs and other design attributes together with their probability of achievement in the final design. Uncertainties may be aggregated and levels of uncertainty in different parts of the model may be continually analysed and assessed. The framework also provides a mechanism for accumulating product knowledge, in particular knowledge concerning relationships between elements of part and assembly models, product volumes and manufacturing considerations.

A mathematical model and a heuristic approach for design of the hybrid manufacturing systems to facilitate one-piece flow

One-piece flow is a design rule that entails production in manufacturing cells on a ‘make one, check one, and move-on one’ basis (Black, J.T., 2007. Design rules for implementing Toyota Production System. International Journal of Production Research, 45 (16), 3639–3664), which reduces manufacturing lead time significantly. This paper proposes a sequential methodology comprised of a mathematical model and a heuristic approach (HA) for the design of a hybrid cellular manufacturing system (HMS), to facilitate one-piece flow practice. The mathematical model is employed in the cases of small- and medium-sized problems, and it attempts to minimise the total number of exceptional operations, while considering machine capacities and alternative machines. The machine-part matrix achieved by the mathematical model is input into the flow line design stage of the HA, where backflow within the cells is eliminated. However, for industrial problems, the proposed HA is utilised. After the formation of the cells by clustering, the HA attempts to eliminate exceptional operations of a given cellular configuration together with a functional structure by employing alternative machines, based on the decision rules developed. Later, unidirectional flow within the cells is achieved and the capacity and budget constraints are satisfied. A medium-sized problem is solved by using both of the approaches, namely, the model integrated with the flow-line design stage of the HA and the complete HA. The results are discussed and the limitations are explained.