Tarek AlGeddawy

Assembly systems layout design model for delayed products differentiation

Frequently changing customers’ needs and market pressures motivate manufacturers to offer a wide variety of their products. Poor demand prediction and increased manufacturing complexities and managerial burdens are just a few symptoms of products variety proliferation. Applying a postponement strategy is an effective method for mitigating the complexities arising due to increased products variety and customisation. Delayed product differentiation (DPD) is a prerequisite for applying form postponement strategies, where the unique features that distinguish each product are added at the final stages of production. This paper introduces an innovative design methodology to derive and represent an assembly line schematic layout for delayed products differentiation. The proposed methodology incorporates product commonality analysis and feasible assembly sequences to synthesise the assembly line layout in a single integrated logical design framework, without pre-defining either the number or the positions of differentiation points along the line. Products commonality analysis is performed using cladistics techniques commonly used for biological classification. The classical cladistics was modified to take into consideration the precedence constraints, which are required to ensure the feasibility of assembly sequences. Real product variants are used to validate the proposed DPD assembly line layout design methodology and demonstrate its merits.

Changeability Effect on Manufacturing Systems Design

The changeability of manufacturing systems enhances their adaptation to the increasingly dynamic market conditions and severe global competition. The effect of manufacturing systems changeability objective on their design process is discussed in this chapter at different levels, from the general frameworks, where the main objectives are stated, to the finest synthesis details, where product and production modules are designed. The conventional design frameworks are discussed and critiqued, and the tendency of most manufacturing systems design processes to be uni-directional is pointed out. Furthermore, a new manufacturing systems design framework is proposed to overcome the uni-directionality drawback of conventional design frameworks and help achieve a closer integration of both products and systems design and evolution.

Change in Manufacturing - Research and Industrial Challenges

Change, in products and systems, has become a constant in manufacturing. This sector continues to witness major market shifts, introduction of new materials and processing technologies as well as great changes in consumer preferences and productsvariety. This presents significant challenges to industrialists, researchers and educators alike. Changes can most often be anticipated but some go beyond the design range. This requires providing innovative change enablers and adaptation mechanisms to mitigate the effects of, and capitalize on, changes in manufacturing. Experiential research and learning is essential to enhance responsiveness and prepare production leaders of the future. The training and experimentation could be significantly enhanced if manufacturing systems could be brought into the laboratories of academic and research institutions. This paper describes the latest state-of-the art fully reconfigurable “plug & play” changeable and flexible “Factory-in-the-Lab” infrastructure and supporting design innovation and advanced research environment. It discusses the use of the iFactory and iDesign system to address these challenges and develop many key technologies and strategies for success. It presents severa novel approaches and methods for achieving the desired balance in the wide spectrum of variation in markets, products, processes, systems and manufacturing enterprises.

A model for co-evolution in manufacturing based on biological analogy

Manufacturing systems continue to adapt in order to survive the changing and challenging markets and global competition. Product and manufacturing design and capabilities are configured to allow the needed adaptation through innovative design, improved system paradigms, intelligent design and optimisation models, and product grouping to increase efficiency. In this research, it is hypothesised that the evolution and co-evolution of products and the machines used to manufacture them is akin to that observed in the adaptation of biological species. The symbiosis between products and manufacturing capabilities is studied using real examples, and a new model that establishes the symbiotic relationship between their evolution paths and observed co-evolution trends based on available historical information is proposed. Dual cladograms are used to track their evolution and detect useful potential development and plausible future evolution trends. When a state of co-evolution equilibrium is reached, a stimulus for more abrupt changes would be needed to cause further evolution on both sides. The co-evolution model has been applied to an example based on analysing the history of machine tools development and data from a major machine tools manufacturer. The evolution and co-evolution hypotheses of machined parts and machine tools were charted up to the currently observed state of equilibrium in this application field. This innovative model of co-evolution in manufacturing can help improve the utility of manufacturing resources and prolong the life of manufacturing systems beyond a single product generation and its variants.

New dependency model and biological analogy for integrating product design for variety with market requirements

Variety in product design is a result of diversity of needs in different domains and market segments. The two-way interaction and dependency between product design features and customer requirements is analogous to co-evolution in nature, where two groups of different species evolve to co-exist. A new method for designing products, families and platforms by recognising commonalities and core features, using the concept of co-evolution, is introduced in this paper. Cladistics is used to identify product component modules which correspond to common regional market requirements. Algorithms for functional and structural analysis as well as product variants generation have been developed. Complex dependency interactions and modularity relationships are modelled using liaison graphs and cladograms. A case study of washing machines is detailed and used to validate this novel application of the co-evolution dependency model in product families and platform design, demonstrating its use in the world of artefacts co-development. The proposed model is capable of satisfying different market segments’ requirements, while minimising the cost associated with product variety, by promoting modular product family design. It selects the best product variant(s) for each market segment and minimises component redundancy.

Multidisciplinary Domains Association in Product Family Design

This chapter presents an innovative new model for integrating the diversity of market segments requirements with the design of product families and platforms for achieving mass customization. It is hypothesized that the relationship between product design features, product functionalities, and customer requirements domains is analogous to species co-speciation in nature. Each “Market Species” represents the needs of a market segment in the customer domain, satisfied by a group of product functionalities that are associated with a group of product components forming the corresponding “product Species” (variant) in the physical domain. Co-speciation is studied in biology using the reconciliation of cladogram trees, which result from cladistic analysis of the studied species characteristics. Cladistics is used in this work to build products platform and modules which correspond to the common regional requirements of the market. Design Structural Matrices are used to capture the relationships between the three domains, while liaison graphs help avoid infeasible combinations of product components and infer possible components integration. This model is useful in products mass customization applications, where delayed product differentiation is a prerequisite, as it allows synchronizing the differentiation points in different domains to maximize the benefit from commonality of requirements, functions, and components.

Determining Granularity Level in Product Design Architecture

Product architecture represents components grouped into modules that can be assembled later to constitute a specific variant. Literature provides Methods of clustering components into weakly related modules with strong interconnections between components within modules. The number of modules and their hierarchical relationships shape product architecture and determine the balance between modular design and components integration. A novel hierarchical clustering approach, based on the biological Cladistics analysis, has been developed to cluster Design Structure Matrix (DSM) widely used to promote modularity. It evaluates different granularity levels of the resulting hierarchy and finds the best granularity level for maximum modularity. An automotive Body-in-White of 38 different components is used as a case study. Results showed the superiority of the recommended modularity pattern and synthesized product architecture over other clustering techniques.