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Knowledge Domains in NFTDC

The three major macro knowledge domains of NFTDC are

  • Advanced Materials and Processing

  • Design, Analysis and Advanced Manufacturing (CAD/CAM/CAE/RE/RP)

  • Instrumentation, Electronics & Control (ICEL)

All projects of NFTDC rely extensively on engineering design of components and systems. These three macro domains are further broken down into multitude of sub domains which form the cumulative core competence of NFTDC. Each of these domains is mapped as equipments & laboratories and knowledge competence in individuals and together they are brought together in project teams to address the output. The following give the approaches which have evolved in NFTDC over a period of time.

Materials to Components to Systems: NFTDC’s Approach:

Product design and development can be characterized by and understood in terms of (i) systems approach wherein the final output is the starting point and ‘output based planning of inputs’ in contrast to ‘input constrained output’ becomes the basis; (ii) multiple knowledge inputs and interdisciplinary cross linking, in other words knowledge integration; (iii) creative (visualization) processes on the one hand and physical, engineering, information and biological processes on the other; and (iv) it follows the evolutionary paradigm (differentiation-selection-multiplication). In this presentation, an attempt is made to show that knowledge creation and knowledge integration paradigm and the evolution paradigm form the basis for product creation endeavours involving complexity and variety.

Definition of a Product:

A Product is defined not as a physical entity. It is better defined as a designed output created by a series of processes (by natural evolution or human intervention) to meet functional performance(s) in the required service conditions over a life span and be capable of reused/recycled/reclaimed after its life span. The product can be ideas, abstracts and constructs which are the results of creative and visualization processes, simulation and virtual models, proof of concepts, prototypes and working models.

Knowledge Domains & Micro Domains:

Physical sciences & engineering Sciences over the last few decades have progressed to encompass a comprehensive knowledge base of structures at various levels (atomic to nano to micro to macro), processing methods and the set of achievable properties. These inter relationships were well understood that the mapping across these three domains and reversibility became possible. This in turn allowed “design” of material(s) and products in hierarchical structures, which can be rendered by engineered processes (sequenced and optimized) to give the performance over its life span in the required service conditions. Materials by design became a realistic goal thanks to the understanding of patterns of structure (pattern recognition) and their relationship to performance and their rendering as synthesized patterns (processing). The design of a material product which was considered in macroscopic terms of mechanical design graduated to micro structural design and is now progressing also into nano structural design. The top down approach which is engineering design base and the bottoms up approach of physical sciences are now better understood and the product design starts in the former as an adaptive walk by carefully dovetailing advances that come from bottoms up approach. Energy Device developments such as solar cells, batteries and fuel cells are the best examples. The knowledge data base in various disciplines of engineering can be considered as a large set of micro knowledge domains. An example of a micro domain would be the physical basis of stiffness/modulus and the relationship between bonding (stiffness of various bonds) at the atomic level to micro structural features to stiffness as understood in a cantilever beam. Similarly, process methods and process parameters to optimize the size and shape of porosity and the interconnecting matrix or ribs to obtain a range of structures from foams to full density materials and mapping of various relationships to a host of properties can be another micro domain. Design processes starting with visualization, to computer aided design, analysis, rapid prototyping and large number of manufacturing methods forms a large set of micro knowledge domains. System design and engineering is considered in many ways such as in sub systems and interfaces, as a network of mass, energy and information flows, pattern synthesis and so on. Product at systems level needs control. For example an electric vehicle whose propulsion system is based on a motor + controller + energy device combination as a system and electronic control units (ECUs) form the vital part of the overall system architecture. Likewise thousands of micro knowledge domains can be elucidated.

Differentiation & Knowledge Integration in the Design Process

The design of the product now can be broken up into “desirable or required” attributes and each of these attributes can again be mapped on to one or a combination of knowledge micro domains which form the scientific know-whys and know-hows. Reintegration of these micro domains on a solution path (determined by the fitness function which includes attributes plus a host of economic and market related factors) gives the successful design and its rendering methods. It is noted here that both know-why (scientific basis) and know-how (methods and processes for rendering) are considered as knowledge domains. Thus the product creation process can be surmised as “differentiation” followed by “integration” of knowledge domains. This perspective also neatly dovetails with the systems approach wherein the “output” is taken the ultimate goal and it is broken up into multitude of domains and the inputs are required in each of the domains and its sub and micro domains are understood/created/developed/outsourced and reintegrated to obtain the final output. Further insight into this process would reveal that as we differentiate more and more (multitude of micro domains), our design space increases and the possible solutions also increase. The solution is chosen by the fitness function which is equivalent to selection in the evolutionary biological systems. Key to innovation lies to enumerating this design space and figuring out the combination of relationships that best capture the required attributes which we call here as knowledge integration exercise. The origin and cause of complexity with variety lies in this largeness and expansive characteristic of the design space.

Industrial Design

Rather than considering the design of a product from an engineering angle, let us take get into the shoes of an industrial designer. An industrial designer plays the role equivalent to that of an architect who envisions (visualizes) and enables integration of forms, structures, materials, aesthetics, ergonomics and all attributes with functions. From the perspective of an industrial designer, a design is nothing but an optimized set of relationships between the attributes. A successful design is one that has captured all the required attributes. Functional performance, service conditions, life span, 3R (reuse, reclaim and recycle) are treated as required attributes. But the industrial designers go many steps further to include many other attributes such as aesthetics (style, texture, visual appeal, emotional and psychological responses), ergonomics, relationship between the user and the product, market forces, perceptions etc. These added attributes bring about multitude of variants around the basic attributes. Thus there is a design space that gets enumerated by attributes and as the attributes increase, the combinations increase exponentially. Though the design possibilities in this space are large, four extremes nodes are easily enumerated and one can conceive a design space bounded by these extremes. A design can be minimalist. In other words, it satisfies bare minimal requirements and many of higher level functional requirements are not met. Subtraction of this minimal set would result in a null set. The next level node is functional design wherein all the functional requirements are met which is basically an engineering design. Third level is the aesthetics node, wherein, the style, visual and emotional appeal are given significant or sometimes higher weight than the functional aspects. Lastly, it is the esoteric or hedonistic design wherein the design is not for functional purpose but more a projection of personality of the user. While the design space is large, we find that most of the designs will fall between minimal to functional with extension to aesthetic domains.

Design for Manufacture

Industrial design has taught us tools and techniques to abstract the attributes and enumeration of design space. Exploration of design space gave innovative solutions to achieve the attributes. This has to be taken further to encompass a design process that lends itself for manufacture (process know –how). Design for manufacture (DFM) takes the process methods and process knowledge domains into consideration in the design process itself. Innovation is also possible in process methods (hybrid processes are an example) but the process innovations are fewer and far between. Materials science and engineering in that aspect has embedded the process know – how as an integral part of the knowledge relationships. Process methods, regimes and process equipments, their capacities and capabilities give the added dimensions in the design space. It is finally the processes that give the know-how for manufacturing and manufacturing has to be in multiple scales (atomic to micro to macro) and it has to synthesize the hierarchical structures of the designed output.

Design and 3Rs

While the functional requirement in the service condition over the designed service life was paramount for decades, the 3R requirements (reuse, recycle, reclaim) and the impact of a product on the environment have become important attributes in the fitness function. Design for disassembly, safe disposal, standardization of materials, minimization of variety becomes higher weighted attributes in the fitness function. The design processes will now be dictated by these fitness functions of the habitat more and more and the next generation solutions will come more from materials that meet the 3Rs. The process know-how that renders these designs should meet the requirements of energy conservation and minimal environmental impact for sustainability.

Materials World and Biological World: Evolution as a grand design

Evolution has taught us the paradigm of differentiation (design space), selection (fitness function for sustainability and the best adaptation to the habitat) and multiplication (amplification or bulk manufacture). Complexity and variety, self learning and self organization have been the hallmark of this paradigm. Design of materials and materials products which are now understood in terms of materials, mechanical, electronics & controls, information and biological sciences domains can be considered as multitude of knowledge micro domains of know-whys and know-hows in the design space and the solutions that satisfy the fitness function emerge from these domains. The explosion of technology and the products of technology reflect the complexity and variety in the materials product world akin to the biological world of species. This gives us the necessary pointers for our future endeavours in the materials and design and control of systems.