Platform product development is a contemporary approach to agile product development for mass customization. Distinctive product variants are derived or customized from a platform that is defined as components and subsystems commonly shared across a product family. A well-organized platform is essential to connect different parties of an enterprise including soliciting customer needs through order fulfillment to field service. Hence, it is also critical to achieve the economy of scale by identifying repetitive applications of share tooling, knowledge, and other resources. In this Special Issue, we attempt to cover the different aspects of platform product development. The topics span a wider range of artificial intelligence (AI) disciplines, from knowledge representation to knowledge support systems. It identifies a fertile area not only for applying AI to contemporary issues of design and manufacturing systems but also for enriching the methodology for developing AI systems in manufacturing enterprises. Indeed, we consider that numerous successful applications in the industrial sectors highlight a future direction for productive AI applications in industry.

In an effort to improve customization for today's highly competitive global marketplace, many companies are utilizing product families and platform-based product development to increase variety, shorten lead times, and reduce costs. The key to a successful product family is the product platform from which it is derived either by adding, removing, or substituting one or more modules to the platform or by scaling the platform in one or more dimensions to target specific market niches. This nascent field of engineering design has matured rapidly in the past decade, and this paper provides a comprehensive review of the flurry of research activity that has occurred during that time to facilitate product family design and platform-based product development for mass customization. Techniques for identifying platform leveraging strategies within a product family are reviewed along with metrics for assessing the effectiveness of product platforms and product families. Special emphasis is placed on optimization approaches and artificial intelligence techniques to assist in the process of product family design and platform-based product development. Web-based systems for product platform customization are also discussed. Examples from both industry and academia are presented throughout the paper to highlight the benefits of product families and product platforms. The paper concludes with a discussion of potential areas of research to help bridge the gap between planning and managing families of products and designing and manufacturing them.

Product families help companies reach customers in several different markets, lessen the time needed to develop new products, and reduce costs by sharing common components among many products. The product platform can be considered as a set of technologies, components, or functions, and their arrangements, that are utilized for more than one product. Configuration design focuses on the components in a product and their connections and relationships. Discrete, combinatorial design spaces are used to model design requirements regarding physical connections, module partitions, and assembly sequences for the product family. To ensure that products satisfy all design requirements, it is necessary to combine these design spaces into a common configuration space into which all requirements can be mapped. This paper presents computational methods for modeling and combining design spaces so those configurations can be identified that satisfy all constraints. A new representation of assembly sequences facilitates the development of an assembly design space, elements of which can be enumerated readily. Because the size of the combinatorial design spaces can become quite large, computational efficiency is an important consideration. A new designer guided method, called the partitioning method, is presented for decomposing configuration design problems in a hierarchical manner that enables significant reductions in design space sizes. An example of a family of automotive underbodies illustrates the application of the discrete design space approach to develop a common platform.

The use of modularity in the design of a new product or the adoption of a product platform, as the base to define new solutions within a product family, offers the company a chance to meet diverse customer needs at low cost because of economies of scale in all phases of the product's life cycle. At present, the concept of modularity in product design is becoming widely used in many industries such as automobiles and consumer electronics. However, if modularity and mass customization have attracted the interest of industries and researchers, the greatest efforts have been focused on the theoretical aspect whereas the related design support technologies have been only partially implemented. In this context, our intent is to develop highly reusable models, which are able to reconfigure themselves on the basis of new functional requirements. The proposed approach is based on the definition of what we call self-configuring components and multiple-level functions. To describe the approach, a practical example related to the design of modules for woodworking machines is reported.

In their quest to manage the complexity of offering greater product variety, firms in many industries are considering platform-based development of product families. Key in this approach is the sharing of components, modules, and other assets across a family of products. Current research indicates that companies are often choosing physical elements of the product architecture (i.e., components, modules, building blocks) for building platform-based product families. Other sources for platform potential are widely neglected. We argue that for complex products and systems with hierarchic product architectures and considerable freedom in design, a new platform type, the system layout, offers important commonality potential. This layout platform standardizes the arrangement of subsystems within the product family. This paper is based on three industry case studies, where a product family based on a common layout could be defined. In combination with segment-specific variety restrictions, this results in an effective, efficient, and flexible positioning of a company's products. The employment of layout platforms leads to substantial complexity reduction, and is the basis for competitive advantage, as it imposes a dominant design on a product family, improves its configurability, and supports effective market segmentation.

One of the aspects of mass customization is to provide customers with products that are manufactured to their needs and requirements. To provide such support requires better integration of the customer into different stages of design and manufacturing. Expansion of the Internet provides an opportunity for such an integration, which will need to link design and manufacturing of the company with the customer. In current approaches, customers usually specify the options and get the price or simple pictures of the object. In this paper we present a framework in which customer options and size parameters are gathered using the Internet. It is used to automatically generate a 3-dimensional computer-aided design model of the product, estimate the price of the product, and generate assembly sequence information. The framework for mass customization of products necessitates information management among different segments of the company and the customer. The Internet-based system presented in this paper uses a graph grammar and templates to explicitly maintain correspondence among various types of product information from a module perspective. The system is demonstrated using a customizable coffeemaker product family.

Mass customization has been identified as a competitive strategy by an increasing number of companies. Family-based product design is an efficient and effective means to realize sufficient product variety, while satisfying a range of customer demands in support for mass customization. This paper presents a knowledge decision support approach to product family design evaluation and selection for mass customization process. Here, product family design is viewed as a selection problem with the following stages: product family (design alternatives) generation, product family design evaluation, and selection for customization. The fundamental issues underlying product family design for mass customization are discussed. Then, a knowledge support framework and its relevant technologies are developed for module-based product family design for mass customization. A systematic fuzzy clustering and ranking model is proposed and discussed in detail. This model supports the imprecision inherent in decision making with fuzzy customers' preference relations and uses fuzzy analysis techniques for evaluation and selection. A neural network technique is also adopted to adjust the membership function to enhance the model. The focus of this paper is on the development of a knowledge-intensive support scheme and a comprehensive systematic fuzzy clustering and ranking methodology for product family design evaluation and selection. A case study and the scenario of knowledge support for power supply family evaluation, selection, and customization are provided for illustration.