By 2030, designers will work synergistically within design environments focused on design not distracted by the underlying computing infrastructure. Designers will interact in task-appropriate, human terms and language with no particular distinction between communicating with another human team member or online computer design tools. Such environments will amplify human creativity leading towards innovation-guided design. Future design tools and methods will not only support analysis and decision making from a technological point of view, but will also account for psychological, sociological, and anthropological factors based on fundamental understanding of these factors and their interaction. Instead of just designing products and systems, designers will be concerned with design of the total experience. Design of system of systems will supersede the design of individual systems. This will lead to reduced uncertainty in engineering design and greater confidence in the design process. Fundamental realignment in design learning, teaching and thinking need to change accordingly to maintain the nation’s economic competitiveness and improve the quality of life for people around the world.

Keywords: Engineering innovation, Social-technical aspects of design and Design informatics


This paper presents some of the interesting revelations on future forecasts in engineering design research and its impacts. This work is drawn from activities of Faculty Design Teaching Forum (DeKUT). 

Engineering design is a socially-mediated, technical activity that creates and realizes products, systems, and services that respond to human need and social responsibilities. Human behavior dynamics affect design decisions that cause societal changes, which, in turn, shape human and social dynamics to influence future design decisions. Such adaptive, cyclic socio-technical interactions represent the fabric of modern technological and societal development. Understanding the social aspects of engineering design, which underline these dynamic socio-technical interactions is, therefore, critical in future design research. Developing such an understanding has become an urgent task in the 21st century, when the speed and frequency of human interactions and societal changes have been greatly amplified by the internet revolution.

Fundamental developments in design tools, methodologies, learning, teaching and thinking need to change accordingly to maintain economic competitiveness and improve the quality of life for people around the world. Innovations in product design, manufacturing, information technologies and utilization of emerging technologies demands transformation and advancement of engineering design tools and methodologies. These are the main issues at the core of research in engineering design.

This paper is organized into four sections namely; background, approach, discussion and lastly conclusion.


Holistically, engineering design may be described by components that include understanding the markets and product requirements, devising clever innovative solutions, and efficient product realization processes to ensure fast time to market and better quality. These may be broadly aligned in three dimensions namely; innovation science, Socio-technical aspects of Engineering Design and Computing & IT infrastructure for Engineering Design:

Innovation Science

In reviewing the past 20 years of the Engineering design Program, we find that the focus has been on improving existing (known) products and processes [1]. Figure 1 shows uncertainty map in engineering design with respect to innovation. Certainly, innovation is needed in all areas represented in Figure 1, but the greatest opportunity lies in the region toward the top right: discovery of innovative products and processes. In the lower left, typical of the auto industry, both the product and the realization process are well known, but innovation is still urgently needed in tools for continuous improvement.

Figure 1: Engineering Design Innovation and Uncertainty

The upper right by contrast has the innovative idea in place but needs innovations in the design process and possibly in the manufacturing process. The upper right quadrant is the most in need of innovations – it is referenced as “The Fog.” Here, inventors are struggling to invent the next innovative product.

Innovation should occur in all areas of an enterprise. At one end of the spectrum, Toyota is famous for encouraging the daily, individual-human-inspired innovation. Even the lowest level, already well-known task is constantly re-evaluated for potential improvements and innovations. At the other end of the spectrum, famous innovators in automobile styling, aircraft design, consumer electronics, and personal products try to “Surprise and Delight” us with new products that literally will “jump off the shelf and sell like hot cakes

Socio-technical aspects of Engineering Design:
Engineering design is a socially mediated technical activity that creates and realizes products systems, and services that respond to human need and social responsibilities. It is a technical activity, which must meet human purposes and social responsibilities. Human behaviour dynamics impact design decisions that cause societal changes, which, in turn, shape human and social dynamics to influence future design decisions.  Such  adaptive,  cyclic  socio-technical  interactions  represent  the  true  fabric  of  modern engineering design.

Figure 2 Harmonization of social and technical aspects of engineering design

When multiple stakeholders interact to make design decisions for competing product life-cycle concerns, both concurrent and collaborative engineering approaches are useful. However, we must understand the intrinsic difference between the two. While concurrent engineering attempts to maximize parallelism for interacting but separate design tasks, collaborative engineering requires all stakeholders collaboratively negotiate a single joint decision. Since there is only a single decision to make in collaborative engineering, the challenge shifts from sequencing multiple decisions to negotiating a single agreement – a technical decision task that is heavily influenced by human and social dynamics [2]. While game theories have been developed to address separate but interacting decisions, new negotiation theories are needed to support joint decisions in socio-technical collaborative engineering design.

Additional socio-technical aspects of design involve:
•    The efficient organization of globally distributed, inter-disciplinary teams to optimally communicate and collaborate.
•    Tools/techniques for formulating design requirements in a global economy, mass customization, and cultural/economic diversity

The objective of Engineering design will be to develop basic knowledge to support the socio-technical aspects of engineering design, such as the effects of new products and technologies on society, and vice versa. Socio-technical studies are essential in defining product requirements, particularly in culturally diverse populations. Our mission should be to develop a multi-dimensional paradigm that truly combines the technical (i.e., what-how) and the social (i.e., who-why) dimensions of engineering design. This Socio-Technical Engineering Design Paradigm suggests that future engineering design must be researched, taught, supported and practiced as a common concern by all in the society, rather than a specialized skill for the few.  They have many important implications in future design education, research, and technology development.

Computing & IT infrastructure for Engineering Design:

Engineering design is a discovery process that requires: exploration to develop a clear understanding of the problem, knowledge and skills to synthesize and predict the future outcome of a design. Often, design still relies on knowledge gained after many years of practice. As products become more complex, traditional engineering methods and know-how will not be sufficient and must be enhanced or replaced with new methods and tools. The knowledge used during design (rationale) is currently not captured in any consistent form that it can be reused other than by the person who recorded it, if any records were kept at all. As a consequence, many components have to be reinvented each time a new product variation is realized. Capturing the knowledge used in a way that does not hinder the designer and then providing the tools to re-use and reason with this knowledge will reduce time to market [3].

The most successful designs are often the result of exploring many alternatives. However, due to time and budgetary constraints this explorative stage is often curtailed. With the advent of virtual prototyping and validated physics based simulation tools the design process can be carried out within a project’s constraints covering a wider range of realizable design alternatives and therefore increasing the chance of creating novel designs.

Major components of Engineering design contents and requirements have been identified through literature review and also drawn from experience from members of (DeKUT). The process went through series of consultative forum activities and meetings. These include consultative meeting with the Engineering professors from The Wildau University of Germany during their visit to Kenyan Universities, consultative meeting with visiting professors from Kyushu University and Totori University of Japan and industry focused reviews carried out and presented by (DeKUT) at the DeKUT School of engineering seminars. The Key idea was to have a clear state of affairs in engineering design practice and education with concerted efforts to pointing out the gaps that still remains as major constraints in engineering design progress.


These are not official industry reviews or the corresponding industry sectors; they are views expressed in various reliable articles, documentaries and members invited to our forum who are informed about these companies. Nevertheless, they provided useful insights to the forecasts on the future of engineering design.

The details of the reviews cannot be included here; a brief summary is given below.

Aviation industry (USA case)
The US aviation industry is increasingly focused on a system-of-systems approach to design. This means different things to different people but the main thrust is how to design around multiple cooperating and counteracting components to coordinate them and optimize certain objectives.

For civil aviation, the system-of-systems approach is focused on redesigning air traffic control and airplane avionics to initially deal with growing traffic while increasing safety, enable free flight and finally enable autonomous operations. This is a very challenging task because of existing systems, regulations, cost of required infrastructure, and diverse range of things that float in the air (from balloons to supersonic military jets). Free flight will enable commercial airline operators to account for winds aloft to determine flight paths that minimize fuel burn or travel time, versus following predetermined air-routes as is the case today. Autonomous operations demand a very complex system-of-systems to handle air traffic control and be externally resistant to destructive subversion.

Advances in electronics and computational power will lower the cost of avionics (currently about 1/3 the price of an airplane) and provide affordable advanced avionics to light aircraft. This will be one of the main drivers to open Personal Air-Vehicles (PAV) to a larger segment of the population. PAVs necessarily have to fly autonomous along “highways in the sky” because instrument flight is complex, hard to learn and hard to remain proficient.

On the military side, the system-of-systems approach is exemplified by Future Combat System (FCS) and Network Centric Warfare. The intent is to design a more effective combat system by increasing battlefield awareness with redundant communication between the components and provide control and optimized allocation of heterogeneous resources.  Part of the challenge here is determining what these future resources will look like and what capabilities they need.

Domestic air travel is expected to triple in the next 20 years. To respond to that demand a larger diversity of configurations and sizes will be built. Commercial transports are likely to resemble current configurations, but may eventually include others such as the more efficient blended wing body (the flying wing) if it can pass passenger acceptance. The desire, attractiveness and need for personal and on-demand point to point travel will increase. The optimum vehicle type will depend strongly on range. Short-range vehicles will place a premium on small environmental impact (mostly noise) so that they can operate in close proximity to dense populations. These smaller aircraft must be able to land and take off from short runways. We may see configurations that range from the conventional to hybrid airplane- rotorcraft that can take off like a helicopter but fly like airplanes.

Reliability and cost of maintenance is another important factor that will play a crucial role for making smaller aircraft succeed on a larger scale. The retirement of the Concorde put an end to commercial supersonic travel. Demand still exists for those that put a high price on time but the sonic boom and emissions remains the major obstacle to conquer. Studies are currently underway, called Quiet Supersonic Platform (QSP), to mitigate the intensity of the sonic boom through shaping, with business travel as the first potential market. Further into the future are hypersonic vehicles that can reach any destination in the world in under two hours.

With the increased emphasis on a global economy, cargo transport is expected to triple in the next twenty years favouring growth in large aircraft. To compete with road and naval transport while offering a speed advantage, advanced dirigibles and ground effect planes for trans-oceanic travel are under consideration. Military cargo planes are likely to be the first to be flown without pilots, with commercial cargo to follow. The market size for cargo is very sensitive to the rate charged. An airplane design that substantially lowers the cost will expand the market.

The Pentagon estimates that by 2020 a third of all US combat planes will be unmanned and autonomous. The future will explore different UAV configurations and sizes (over 200 feet to 6 inches and under) to meet different intelligence gathering and remote sensing needs. Because UAVs do not have to accommodate people, the benefits are enormous. Commercial applications of purpose build UAVs will include: low cost alternatives to communication satellites that hover over cities; cargo transport; fighting fires and rescuing people; and conducting aerial surveys.

Environmental concerns will lead to alternative fuel sources like hydrogen to power jet engines. Hydrogen unfortunately requires twice the volume of jet fuel and needs to be stored in pressurized vessels requiring different airplane configurations. Solar cells will power lighter UAVs whose main task is to loiter over an area for long periods of time. Nuclear fuel is another possibility but unlikely to materialize in the next 25 years due to technical, political and security reasons. Materials technology plays a major role in determining the capabilities of an aircraft. Future aircraft will increasingly use composite technology, with nano-tubes as a distant possibility to achieve an additional order of magnitude gain of strength over weight. Airplane skins and structures will be instrumented to detect damage and later provide the ability to heal or change shape.

From a design standpoint the future aviation industry represents an immensely complex and poorly understood design space littered with a high degree of uncertainty. The design objectives are often characterized by ill-defined mission statements and vague measures of merit. After all, it is hard to know what you can do until you try it and figure out the cost and it is hard to fathom the market for something that does not exist.

Space industry (NASA)

US space exploration is driven by three forces: the vision set by the White House, the Department of Defence (DOD), and commercial application. The White House has set a vision to extend human presence to the Moon by 2020, followed by human exploration of other destinations in our solar system [5].

The lofty plan is to establish a base on the Moon started in 2008, using autonomous robots to assemble and build the required infrastructure before humans arrive. Once the Moon base and the essential life support logistics are in place, extended humans expeditions on the lunar surface will start. Preparations will then commence to support sustained human space expeditions to Mars, and beyond. Similar to the mission to the Moon, autonomous robots will establish the required infrastructure (shelter, power generation, food, air) to sustain human life on Mars. Along the way, several safe havens will be established in case of malfunctions. The Moon base may be used to assemble and launch missions to other destinations to take advantage of lower gravity.

Some of the mission capabilities identified to accomplish this vision are:
Autonomous operations for all aspects of a mission: These include orbital control; logistics & maintenance: delivery of supplies to remote destination, repair of equipment; Obstacle & hazard recognition; autonomous exploration and building the infrastructure to sustain human presence.

Durable robust habitats: sustain human life in the presence of radiation and micro-meteorites.

Modular adaptable construction elements: determine the construction elements to build habitats and other space ships. Rockets are limited in payload size requiring larger items to be shipped in pieces and assembled in-situ.

Scalable operations: control missions of different scales using the same infrastructure (e.g., launch a satellite, conduct a mission to Mars). This is a system-of-systems problem.

Robotic operations: Autonomous robots are required to build and maintain the infrastructure on remote locations. They must be able to work together in robotic networks and be reconfigurable to take on different tasks.

The  downstream  benefits  of  this  plan  are  the  gain  in  knowledge  of  space  exploration,  technical innovations and the establishment of the infrastructure for commercial exploitation. Space tourism has been in the news because of Spaceship One’s success to reach 100 km twice in less than two weeks in a reusable vehicle. The true market potential for risky space tourism remains uncertain.

Space exploration on the military side is largely classified. Most work surrounds defending military satellites against threats, space offence and space reconnaissance.

Current space explorations are fantastically expensive and carry a high degree of risk and uncertainty. To accomplish the stated mission by for a reasonable cost, safely, and in the given time frame, requires many inventions and break-through processes in all aspects of science, engineering, design and manufacturing. The expertise to accomplish large space missions needs to be regained.

Automotive industry (GM case)

The regulations related to emissions and the depleting supply of oil requires auto companies to go towards greater fuel efficiency cars with drastically low emissions. The auto industry has realized that batteries will never get to a point where pure electric cars will be viable (poor performance, limited range, high cost). Several lines of development are proceeding in parallel. These include gas-electric hybrids, diesel or diesel-electric, hydrogen power, compressed or generated on board.

The enabling technologies needed are fuel cell/hydrogen, By-wire, new sensors and control systems, integration software, and new forming processes. The auto industry expects future vehicles to be of stunning design, thrilling performance, drastically lower cost, with zero emissions, diverse power sources, safe and easy to use. Hydrogen fuel cells have now reached 1.25 kw/kg, 1.75/l and peak power of 125 kw. The target is for 2 kw/kg.

Safety concerns will lead to smart, adaptive vehicles, which will be aware of their surroundings (Telematics). Drive by wire technology will relieve drivers of mundane tasks. The powertrain is expected to be “electrified”.

Consumer electronics (HP)

The consumer electronics industry products are increasingly becoming a hybrid of mechanical, electrical, wireless and software elements. There is high pressure to reduce device size and improve aesthetics, which necessitates mechanical, electronic and software engineers to work closely. Moore’s law appears to apply not just to semi-conductors but also to electronic gadgets.

The world of electronic products is fast paced, with shorter and shorter product life cycles and greater product variety. Just in the past decade, large markets have been created for products that did not even exist before. Examples include PDAs, MP3 players, multi-media players, GPS navigation devices, digital cameras, DVD players/recorders, picture phones, LCD televisions/monitors, game devices, and so on. Another trend that appears to be evident is the blurring of boundaries between products that were distinct before (e.g., television and Internet), and hybridization (cell phones that can also serve as camera, navigation device and PDA).

It is not impossible to forecast what new devices may come into being in the next 25 years, but it is certain that there will be many. Thus, the very existence of electronic companies depends on their ability to innovate. Failure to do so may make today’s market leader disappear because of obsolescence of its products. Companies such as HP are using formal methods, such as Lateral Thinking and TRIZ to do innovation on demand. The combination of devices through common functions (e.g., 4-in-1 combo of printer, copier, scanner, fax machine) now appears obvious, but why did it take so many years before such a product was developed? Why did a company like HP not invent 3D Printing, a process used for rapid prototyping?

Engineering software (CPD Associates case review)

Engineering software for product design can be broadly classified into three groups:
CAD systems for product geometry definition and visualization, CAE systems for engineering analyses and simulation of behaviour and PDM/EIM/PLM systems for managing electronic data/information related to each product

CAD systems have come a long way in the past 25 years, evolving from 2D wireframe drafting systems into parametrically driven 3D solid modellers. Advanced surface representations, such as NURBS, allow almost any shape to be modelled accurately. However, modifying surfaces is still tedious and non-intuitive. Most CAD systems of today can be described as 2D constraint based and 3D history based; the use of history trees in modifying solid models results in unexpected results. Due to mergers and takeovers, there has been a consolidation of CAD companies: there are only a handful of companies left in the market. The CAD systems offered by these companies are beginning to have very similar capabilities; there have been few major developments in CAD in the past 5 years. This may be because CAD companies have virtually no R&D resources in-house, profit margins have shrunk, and CAD systems are already mature.

Although the IGES and STEP standards allow models to be exchanged between CAD systems, there are several limitations and problems. Parametric, feature, constraint and history information cannot be exchanged at present. Also, the redundant nature of BRep models is proving to be a liability in data exchange. Healing technologies have been invented to aid data exchange. In the next few years we will see parametric, feature and history information integrated into STEP. There is a possibility that explicit geometry exchange may be replaced by construction history exchange.

As CAD companies look to expand their markets, there will be a tendency to push CAD further upstream into conceptual and functional design and parametric exploration that would include non-geometric variables. It is not clear what such an expanded CAD system of the future might look like, but it could possibly encompass both generative and variant design. This would require search engines to navigate design repositories of past designs, standard part catalogues and re-usable design procedures. We could conceivably see a synthesis of CAD with KBS shells. Such systems would offer another major side benefit – automated digital archival of the design process and product evolution.

CAE software based on numerical methods such as FEA has been applied for simulation in many application domains: stress & failure, thermal, fluid flow, dynamics, electro-magnetics, etc. Despite advances   on   the   analysis   side,   model   preparation   (pre-processing) including meshing, is time consuming and requires discipline specialists in the loop. Interfacing different types of applications, such as FEA stress with CFD, is tedious due to different data types and formats. These serial processes lead to long analysis cycle times. New technologies on the horizon include multi-physics analyses, multi-disciplinary optimization, mesh-less   or   mesh-free   analysis   and   automated   model preparation using KBS. Contemporary CAE simulation tools are purely analytically based, generally deterministic and geared to detailed level evaluation (hi-fi); it is conceivable that future tools will be stochastic and will combine analytical and experiential knowledge. Models must be developed to support design at multiple levels of abstraction, from conceptual to detail design.

Although today there exist a wide variety of Engineering Information Management (EIM) systems, the original systems (labelled PDM for Product Data Management) were a by-product of CAD systems. Their original function was to organize related CAD/CAE files by parts, versions, and configurations. In the early 1990’s, functions to support archiving of design files and workflow to route these files for approval, release, and change management were added [6]. Many people view PDM systems as glorified file managers because they operate on files and not the data within the files – this represent a coarse level of data granularity. The current emphasis in product lifecycle management (PLM) adopts a more holistic perspective that ties information management and system integration with business strategy, thereby exploring system effects across the full product realization process. Typically, in the past, companies have focused on managing “Released” designs, but this is gradually being extended to work in progress.

New trends in EIM include customized PLM systems created from business objects and processes specific to the company [6]. There is a trend to move away from physical files to shared databases that affords data management at a finer level of granularity – relations can be set up between data elements rather than just files. This trend may eventually evolve into shared knowledge bases.

There is limited inter-operability between CAE systems and the vast variety of these systems has created discipline specific “silos of automation”; information exchange standards need to be extended to all types of engineering analyses and their constituent data types. Data that is not in digital format is often lost, difficult to find and use. Demand for non-obtrusive tools for capturing design information during the product development process will drive CAD vendors into this arena. There is a need to archive all data related to a products life cycle and the whole product, not just selected parts or file types, as is being done today. This would require the development of consistent multi-level, multi-disciplinary data models which can support a wide variety of users and their needs, from specialists to suppliers. Unless the information collected is organized and structured properly, this overwhelming amount of information will actually reduce efficiency of product development rather than enhance it.

Virtual prototyping (John Deere)

Virtual prototyping, the process of creating a product design, a manufacturing process or facility design, and performing other design, analysis, and evaluation activities within a computer-generated, “digital” environment, is evolving rapidly. Rapid advancements in computer hardware and software, and display technologies are fostering wide-spread changes in traditional product development and delivery processes. These technological advances are reducing reliance on physical prototypes and allowing decisions to be made more through predictive, virtual models. Advanced visualization tools and immersive projection technology are now being used in designing, analysing, and evaluating product models and production processes in many industries and have proven value in making business decisions [8].

Based on progress made in the last 25 years in tools applied to engineering, our current use of immersive collaboration technology, and the promise of future computer and display capabilities, it is foreseeable that engineering in the year 2030 will include the following attributes:
–    Design, analysis, and evaluation of a product or manufacturing process will be performed in immersive, virtual environments before committing to production.
–    Product and manufacturing processes will be developed in shared, virtual environments in which collaborative decision making will occur by geographically distributed participants.

–    Critical product and manufacturing process evaluations (e.g., serviceability, manufacturability, operator and product performance, customer acceptance) will be performed interactively from concept to production.
–    Prediction and verification of designs will be largely simulation-based.

Business drivers for achieving this vision of engineering in 2030 include the need to reduce product development time, facilitate better utilization of global resources, facilitate better communication and decision making among multiple stakeholders (marketing, production, design, and customers), increase customer satisfaction through direct involvement in the design process, improve profitability and competitiveness by reducing costs and inflexibility, and improve understanding of important relationships (spatial and complex data) through immersive, multi-dimensional visualization.

Over the next 25 years, it is foreseeable that low cost, high resolution, stereo immersive “wall size” displays will be available; low cost, high performance computer graphics hardware and software will be built specifically to serve immersive collaboration requirements; very fast computational modelling tools permitting design  teams to stay productive  in  immersive  collaboration environments will  exist; all analysis tools will be integrated within an overall simulation suite; and, engineers graduating from undergraduate curricula will have facilitation and social skills needed to perform effectively in immersive collaboration environments with distributed, multi-disciplinary, multi-cultural teams.

The field of engineering design will be a partnership between industry and academia because it is a vibrant, fast-paced field that generates solutions for the betterment of humankind. This scenario lays out a realistic vision for the design and general engineering process in 2 to 3 decades and can be achieved with diligence, rigor, and innovation in the way that research is planned and executed.

Advances in engineering design research will enable us to predict and attain desired performance in future products at known cost, where cost accounts for ecology, economy and equity. In current practice, design engineers hold the responsibility of making the technical design decisions at different physical locations and life cycle periods. Due to the emerging social trends and the rapid development of telecommunication technologies, we believe that engineering design in 2030 will become a much more ubiquitous activity that is collaboratively participated by many different stakeholders across the traditional disciplinary, geographical, and temporal boundaries. By ubiquitous, we mean that the future design activity will take place anywhere, anytime, and by anyone who has an interest in, or whose interests will be affected by, the outcomes of a design. The participants of future design are collectively called “stakeholders”, which represent various social, economic, and technical (S.E.T.) interests that must be incorporated in design decisions. Due to this broad participation, stakeholders will have mixed motives based on which they must collaboratively or competitively negotiate jointly agreed design solutions.

Our forecast implies that future engineering design must be treated, taught, and practiced as a common concern by all in the society, rather than a specialized skill for the few. As will be made clear in this paper, this vision has many important implications in design education, research, and technology development in the future.
•    Future design will be done by a dynamic set of participatory stakeholders, whose interests, motives, background, and expertise are always evolving to influence, and be influenced by, emerging social trends.
•    Future design will be largely driven, and mostly constrained, by sustainability criteria, such as environmental considerations with finite natural resources.
•    The changing definitions and policies of intellectual property right (IPR) will impact on future design, as it becomes ubiquitous and crosses geographical, national, cultural, market, and technological boundaries.
•    Future design must embrace complexity in functions with simplicity in usages in order to achieve an appropriate level of balance between emerging social and technical factors. The “design for more” trend at the present will be replaced with the “design for less” trend in the future.
•    As the “system of system” concept becomes a norm in future engineering design, the complexity will undoubtedly grow faster than the current approaches can handle. New methods/strategies are needed to better understand and manage design complexity.
•    The ethical principles of the next generation will be very different from that of ours, which will impact on how and what design will be done in the future.
•    As our population grows older, engineering design must focus on truly balanced quality of life beyond just narrow functional requirements.
•    Globalization is here to stay and will become a key driving force behind future engineering design.

Research directed at the development of the computing & information infrastructure should receive high priority, both at the Engineering design program level, and in collaborative efforts with appropriate industry players. Given the higher cost of labour, we must be able to design faster and better, to stay competitive. This can only be achieved by giving designers better design and simulation tools, and quick, easy access to relevant knowledge and information. emphasis of the current Particular high priority areas are: (a) Design Informatics for capture and re-use of design knowledge, and ontologies, search engines to support them; (b) integration frameworks and inter-operable, multi-scale, multi-phenomena design and simulation environments that operate at multiple abstraction levels; (c) smart synthesis and analysis tools for generative design as well as deep reasoning questions for predictive product realization without trial and error, virtually eliminating the need for physical prototyping.

We propose that Engineering Design research specifically highlight Innovation. We emphasize projects that study the Innovation process and create tools and methods to support it. Through innovation science, we expect also to create many new product families: e.g. medical products, communication products, travel related products, smart house, and entertainment products, transportation systems that are and feel safe.

The key to successful design in general, requires a deeper understanding of and support for the creative cognitive processes. In addition, the mapping of such cognitive models onto design tools and methods is a critical research direction.

To launch this new focus we forecast that the Engineering Design program embrace the following:

•    Fundamental studies of how human beings innovate
•    Human behavioural models, and processes of innovation in engineering design
•    Tools to facilitate innovation
•    Technologies for innovative synthesis and collaboration among groups
•    Effective methods and practices in ideation and concept generation (exploring) of alternatives
•    Investigation of relation-spaces and solution-spaces
•    Innovation taxonomy creation
•    Education for innovation science; Understanding the relationship between existing education practices and Innovation; Reforming or augmenting curricula to enhance innovation (e.g. Create a Master of Innovation Engineering program much in the same way business schools have created an “MBA in Entrepreneurship”)
•    Supporting “Surprise and Delight” thinking in product design
•    “Ideas without missions” oriented products
•    Behaviour, emergence, evolution of self-organizing systems at all scales and in all fields (bio-, info-, etc)

Engineering design has often been viewed as a synthesis-cum- decision making activity that maps from a set of what (human needs) to a set of how, (engineered artefacts). In the past, this mapping process was limited by a fixed set of what given by the management or marketing, and the how expected from the designer was restricted to technical specifications. On the other hand, marketing departments study the “why” (a market opportunity exists) and the “who” (is the targeted customer). In the future, there needs to be a closer interaction between the “what-how” dimension and the “why-who” dimension to make better design decisions. Treating them separately makes the design process highly iterative, time-consuming, and costly. A new paradigm is needed to directly integrate the two dimensions.

The cyber-infrastructure of 2030 should provide designers with the following types of resources:

•    Design repositories with associated search engines for finding past similar designs

•    Digital libraries for technical documents, books, design procedures, tutorials, algorithms
•    Catalogs of standard parts, devices, materials for sale
•    Consulting services for specialized engineering analyses
•    Synthesis tools for supporting conceptual design
•    Collaboration tools; infrastructure

Design informatics deals with the collection, organization, representation and searching of information and knowledge useful in design. Key research areas are:
•    flexible, extensible ontologies for devices, functions, behaviour, embodiment
•    mechanisms to inter-relate ontologies
•    information management at multiple levels of granularity
•    information exchange standards
•    knowledge capture tools; representation data structures
•    smart search engines

Although CAD/CAE tools have come a long way in the past 25 years, the major hurdles today is the lack of inter-operability between dissimilar tools (e.g., FEA and CFD; Equation solvers and CAD), cumbersome model preparation, often requiring specialists in the loop, and lack of support for conceptual design. The following types of research must be done to create the new design environment:
•    Integration infrastructures for multi-disciplinary synthesis and distributed collaboration.
•    Intelligent constraint management, conflict resolution. Multi-level models: crude models for conceptual design that can subsequently be refined to hi-fi models for subsequent detailed analysis.
•    PDM/EIM systems that go beyond file management, to manage contents based on relationships across models
•    Shared databases & knowledge-bases for design and analysis to replace physical files as the exchange mechanism.
•    Integrated representation and decision support tools using appropriate levels of abstraction including support the full range of design activities and phases of completion

Collaboration infrastructures are necessary but not sufficient; they must be developed in conjunction with smart tools.
•    Development and integration of multi-scale, multi-phenomena (physics) simulation tools for virtual prototyping.
•    Design synthesis tools: models at the right level of abstraction that support early stage design exploration and tools for analysis with incomplete information and uncertainty; this requires “fast” approximate models to support early stage design exploration and tools for analysis with incomplete information and uncertainty.
•    Tools for conjoint exploration of the Requirement Space and Solution Space
•    Integration of quantitative & qualitative models
•    Decision methods and tools customized to all phases of the design process: varying levels of abstraction, information completeness and uncertainty.

In 2030, designers will work synergistically within design environments focused on design not distracted by the underlying computing infrastructure. Designers will interact in task-appropriate, human terms and language with no particular distinction between communicating with another human team member or online computer design tools. Such environments will amplify human creativity leading towards innovation-guided design. Future design tools and methods will not only support analysis and decision making from a technological point of view, but will also account for psychological, sociological, and anthropological factors based on fundamental understanding of these factors and their interaction. Instead of just designing products and systems, designers will be concerned with design of the total experience. Design of system of systems will supersede the design of individual systems. This will lead to reduced uncertainty in engineering design and greater confidence in the design process.

Tools will be aware of the designers’ needs for performance evaluations and will automatically execute integrated multi-scale simulations/analyses accounting for uncertainty and risk, therefore providing information with a known level of reliability to support design decisions.

This vision clearly indicates that technology and tools available in 2030 will radically change the way we do design. With the advent of entire virtual prototyping, the design process can be revolutionized because it can be carried out within the time and cost constraints of a particular project while exploring a wider range of possible design alternatives. Designers will effortlessly and effectively explore vast and complex design spaces. Design will go from incremental changes and improvements to great bold advances. Therefore, design will be an exciting activity fully engaging our full human creative abilities.

In 2030, stakeholders in the design process – who will be distributed around the globe – will work synergistically with computer design tools.

This collaborative environment
•    will enable the development of design requirements – technical, economic, social, and environmental – that can be adapted as the design evolves
•    will enable the generation of solutions based on an understanding of the relationships among the design requirements and their physical actualization and context of use.

Major shift in the Engineering Design Program is needed, moving from tools and methods that make incremental improvements to design quality, cycle time and cost, to high risk, high pay-off research. Also, if we are to capitalize on advances in new technologies, such as nano and bio- tech,  we  must  invest  in  engineering  design  research  to  pave  the  way  for  converting  research  into commercial products.

1.    P. Wright, L. Gutkowski, D. Brei, D. Cegalarek, J. Groza, K. Huebner, A. Kusiak, Y. Jin, L. Leifer, R. Sriram,
       J. Vance, N. Vargas, “FG4 Report: A
     New Perspective on Engineering 
     Design that Specifically Includes 
       Innovation Science”, Sep 20th, 2004.
2.    S. Lu, R. Bengelink, R. Crawford, M. Jakiela, F. Mistree, P. Papalambros, P. Sandborn, W. Seider, C. Shakeri,
         K. Saitou, D. Trees , C. Vogel, “FG3
         report: Social aspects of Engineering
         Design ”, Sep 20th, 2004.
3.    C. Cruz-Neira, J. Vandenbrande, B. Bettig, D. Brown, J. Duncan, M. Ganter, S. Gupta, J. Kunz, R. Neal, M. Shepard, R. Riesenfeld, S. Wall, T. Wu, “FG2 Report: Information & Computing Technology and Tools for Product Development”, ”, Sep 20th, 2004.
4.    “Future of flight”, The Economist, December 11, 2003.
5.    NASA, “The Vision for Space Exploration”, February 2004: //www.nasa.gov/missions/solarsystem/exploren.html
6.    ISO/CD 10303-108, Product data representation and exchange: Integrated application resource: Parameterization and constraints for explicit geometric product models, ISO TC184/SC4/WG12 N940, 2001.
7.    J. Cagan, W. Chen, M.J. Chung, J. Davidson, J. Donndelinger, C. Dym, S. Finger, D. Frey, K. Frutschy, D. Tesar, J. Terpenny, J. Zagajac, Z. Zhao, “FG1 Report: Theoretical Foundations/Design Models”, Sep 20th, 2004.

Leave a Reply