A hybrid approach to machine-tool selection through AHP and simulation

The selection process of a machine tool has been a critical issue for companies for years, because the improper selection of a machine tool might cause many problems having a negative effect on productivity, precision, flexibility, and a company's responsive manufacturing capabilities. Therefore, in this paper, to determine the best machine tool satisfying the needs and expectations of a manufacturing organization among a set of possible alternatives in the market, a hybrid approach is proposed, which integrates an analytic hierarchy process (AHP) with simulation techniques. The AHP as one of the most commonly used multiple criteria decision-making methods is used to narrow down all possible machine tool alternatives in the market by eliminating those whose scores (or weights) are smaller than a determined value obtained under certain circumstances. Then, a simulation generator is used first to automatically model a manufacturing organization, where the ultimate machine tool will be used, and second to try each alternative remaining from the AHP as a scenario on the generated model. Finally, the final alternative is selected by using the unit investment cost ratio, which is calculated by dividing the investment cost per year of each alternative by the additional number of produced units obtained from the simulation experiment of the relevant alternative.     

An approach to conceptual and embodiment design within a new product development lifecycle framework

The design of new innovative products is the result of an accurate and precise management of knowledge sources all over its life cycle, such as technology, market, competitors and suppliers. The work contributes with a framework that shows how the knowledge sources influence in the state-of-the-art and market needs so that they become opportunities for innovating products addressing the whole product life cycle. It provides a systematic path from the early generation of ideas to the production of a new product proposal. Through a deep analysis of previous research works of new product innovation life cycle development frameworks and linking it with knowledge management, strategic planning and scorecards, we came out with a structured contribution. The result considers the concurrent activities and its relationships all the way through the product life cycle that can help in creativity and innovation, combined with a process management proposal. Managing the sources of knowledge in highly dynamic markets and technologies is one of the major difficulties involved in innovative products design and development. The emerging knowledge from external sources is confronted with organisation internal knowledge and experience in order to achieve the first product correct.     

Performance measurement for new product development: a model based on total costs

The modern market is characterized by consumer demand for quality products (at lower prices), reduced time to market, and cost-savings pressures on manufacturers. To survive in this competitive environment, enterprises must be able to manage and measure their performance with respect to new product development (NPD). This paper presents a cost-effective performance-measurement system for NPD. The model is based on the concept of total-costs analysis. This provides a transparent statistical model that assists management and employees to understand the importance of doing things right the first time. The model incorporates the interactions among NPD teams, manufacturing teams, and customers. It also integrates the results of instances of poor quality at various stages of the NPD process, including: (1) development; (2) manufacturing (the internal customer's perspective); and (3) external customers. A total-costs analysis is thus developed and utilized in planning and establishing a measurement system for NPD performance. The model can be used to satisfy both internal and external customers, and to ensure optimal value for investment in NPD teams.     

An integrated fuzzy approach for information technology planning in collaborative product development

Collaborative product development (CPD) processes are generally based on technological infrastructures. Various information technologies (IT) are proposed every day to facilitate collaboration, integration, co-design and co-development processes. In this highly uncertain environment, a systematic methodology is essential to plan the IT infrastructure needed to start and maintain a collaborative process. This study offers an integrated IT planning methodology combining fuzzy quality function deployment, fuzzy axiomatic design and fuzzy rule-based systems. The methodology is tested in a CPD case and the outcome presents an improvement path for IT for each of the collaborative parties.     

Modelling engineering change management in a new product development supply chain

The changes within a new product development (NPD) process are handled differently depending on the stage of the project. The changes during the initial stages of the project are addressed by design iterations, while the changes after the product design is complete are addressed using a formal engineering change management (ECM) process. The ECM process is a complex process, especially under a collaborative environment, where various independent entities work together for a common cause of product development. The interactions between the NPD and ECM processes have rarely been investigated in the research community. In this paper, we attempt to study the interactions between the various NPD and ECM process parameters by modelling the processes and simulated the model to understand the parameter interactions. The organisations in a supply chain have been characterised based on their interactions with the original equipment manufacturer (OEM) during the NPD process. The organisation process templates representing the NPD and ECM processes of each type of organisation in the supply chain have been modelled. The templates have been used to develop a simulation model representing the NPD and ECM processes for a supply chain. The process variables, such as processing rates, resources, resource composition, resource allocation priority, processing quality and phase overlap, have been included in the model. The results indicate that most of the variables and interactions among the variables have a significant influence on the NPD lead time. By identifying the status of?the NPD process, the decision-makers can use these results to develop appropriate management policies to govern their product development projects.     

An approach to functional synthesis of solutions in mechanical conceptual design. Part III: Spatial configuration

These three papers describe an approach to the synthesis of solutions to a class of mechanical design problems; these involve transmission and transformation of mechanical forces and motion, and can be described by a set of inputs and outputs. The approach involves(1) identifying a set of primary functional elements and rules of combining them, and(2) developing appropriate representations and reasoning procedures for synthesizing solution concepts using these elements and their combination rules; these synthesis procedures can produce an exhaustive set of solution concepts, in terms of their topological as well as spatial configurations, to a given design problem.This paper (Part III) describes a constraint propagation procedure which, using a knowledge base of spatial information about a set of primary functional elements, can produce possible spatial configurations of solution concepts generated in Part II.     

A hybrid optimisation approach to configure a supply chain for new product diffusion: a case study of multiple-sourcing strategy

Configuring a supply chain for a new product is a challenging task due to the lack of historical demand data and the dynamic/uncertain nature of the new product diffusion process. An integrated supply chain configuration (SCC) and new product diffusion (NPD) model is developed to explicitly account for the impact of demand dynamics during a new product's diffusion on an optimal supply chain configuration. Our hybrid NPD-SCC model allows a manufacturer to source from multiple suppliers, vendors or modes for its supply chain entities. Such a multiple-sourcing approach not only helps the manufacturer to diversify its pool of suppliers and maintain bargaining power, but also builds redundancy into the supply chain to hedge against potential demand surge and supply disruption during the new product life cycle. Through a case study and a comprehensive computational study, we find that although the single-sourcing solution is able to achieve lower unit-manufacturing cost (UMC), the multiple-sourcing approach is superior to single-sourcing on the overall supply chain performance in the environment with random supply disruptions. By building-in redundancy as multiple suppliers and modes, the resultant supply chain has less chance of being disrupted and achieves higher overall profit on average. We also draw several other managerial insights closing the gap between some supply chain operations and marketing strategies.     

Supply chain risk assessment during new product development: a group decision making approach using numeric and linguistic data

Companies strive to minimise supply chain related risks during new product development as any glitch while developing new products can lead to considerable delay in product launch with severe financial implications. However, many organisations face difficulty in properly assessing the vulnerabilities of their globally dispersed supply chains during the product development stage as no suitable procedure for that purpose seems to be readily available in the literature. The present research is an attempt to fulfil this requirement. A step-by-step approach for supply chain risk assessment during new product development, involving group decision making, is suggested. This approach can use both numeric and linguistic data and helps in determining vulnerability scores for various sub-systems and for each supplier of the most vulnerable sub-system. This is followed by failure mode effect analysis (FMEA) which helps prioritise failure modes of vulnerable suppliers and thus create specific control plans to mitigate supply related failures. Using this approach, organisations can devise control plans to alleviate the supplier related risks during new product development. Although, the methodology is illustrated through an application in aircraft manufacturing, it can also be used in other discrete and process manufacturing industries.     

The role of product feature relations in a knowledge based methodology to manage design modifications for product measurability

During product development, the verification process should already be considered at the design phase to ensure that the characteristics of the product are measured effectively and reliably. Moreover, the verification process may prove more effective if the inspector is aware of the specific designer's intents. The development of the new ISO GPS (Geometrical Product Specifications) standards is mainly founded on these considerations. In accordance with the ISO GPS concepts, previous work developed a knowledge based system named Design GuideLines (DGLs). This system provides the designer with the knowledge concerning the manufacturing and verification procedures/tools and better links the manufacturing and verification processes to the designer's activities/needs. Further research then exploited the DGLs to discover the relations among product features determined by a particular manufacturing process.

This work again uses the DGLs to prove that further relations among product features may also be determined by the verification process. This knowledge helps designers in understanding the consequences of the modifications applied to the product features required to improve the measurability of the product. Moreover, inspectors can better manage the verification procedure knowing these relations among the product features.     

An ISM-ANP approach to identifying key agile factors in launching a new product into mass production

In order to gain a competitive advantage in the globalised environment, a company has to operate with a high level of agility in terms of responding quickly and flexibly to changes in competitive criteria, the market, and customer demands. Agility has become an important strategic factor in competition. When the design stage of an original equipment manufacturer (OEM)'s or original design manufacturer (ODM)'s product is completed, and it starts to enter the mass production stage, a number of uncertain factors are often encountered, which may delay the manufacturing process and lead to lost business opportunities. Focusing on this issue, the present research establishes a hybrid approach to discovering the critical agility factors when launching a new product into mass production. In this research, interpretive structure modelling (ISM) is first utilised to identify the interactive causal relationships of the employed agility factors. Further, an analytical network process (ANP) model is applied to obtain the importance weights of the agility criteria based on the dependence or feedback relationships among the factors obtained from the results of ISM. As a result, both a visualised causal relationship and a quantified representation of the critical agility criteria can be provided to aid managers in effective decision-making.