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The primary objective of design is to achieve the target value of its function. While principles and techniques of Robust Design address the issue of achieving target values in the presence of different types of variations and disturbances, there exists a unique challenge in achieving design targets when multiple response functions are interrelated. In order to overcome the challenge, we must avoid functional couplings and obtain the interrelationship structure as flexible as possible. In the Axiomatic Design process, such interrelationships are represented by coupling terms in a design matrix. From the targeting aspect of design, it is important to achieve a desirable design matrix structure to, first, avoid any functional coupling in a design matrix and, secondly, maximize allowable sequences of adjusting DPs.

To manage the function of a vehicle's engine, transmission, and related subsystems, almost all modern vehicles make use of one or more electronic controllers running embedded software, henceforth referred to as a Powertrain Controller System or PCS. Fully validating this PCS is a necessary step of vehicle development, and the validation process requires extensive amounts of testing. Within the automotive industry, more and more of this validation testing is being performed using Hardware-in-the-Loop (HIL) simulators to automate the extensive test sequences. A HIL simulation typically mates the physical PCS to a closed-loop real time computer simulation of a powertrain. Interfacing the physical PCS hardware to a powertrain simulation requires the HIL simulator to have extensive signal input/output (I/O) electronics and simulated actuator electrical loading.

Two critical milestones that must be achieved during concept design are 1) definition of a product architecture that meets performance, producibility, and strategic objectives, and 2) estimation of the integration risk in each candidate concept. This paper addresses these issues by describing the role played by the producibility members of an Integrated Product Team (IPT) during concept design. Our focus is on the execution of the what we call the “chain method”, which illustrates the structure of function delivery in a concept in a simple pictorial way and helps the IPT to understand the advantages or disadvantages of using a modular or an integral product architecture. The producibility members play a central role in capturing and evaluating the chains for different candidate concepts and decompositions.

The MIT-based Mars Gravity Biosatellite payload engineering team has been engaged in designing and prototyping sensor and control systems for deployment within the rodent housing zone of the satellite, including novel video processing and atmospheric management tools. The video module will be a fully autonomous real-time analysis system that takes raw video footage of the specimen mice as input and distills those parameters which are of primary physiological importance from a scientific research perspective. Such signals include activity level, average velocity and rearing behavior, all of which will serve as indicators of animal health and vestibular function within the artificial gravity environment. Unlike raw video, these parameters require minimal storage space and can be readily transmitted to earth over a radio link of very low bandwidth.

A human-centered systems analysis was applied to the adverse aircraft weather encounter problem in order to identify desirable functions of weather and icing information. The importance of contingency planning was identified as emerging from a system safety design methodology as well as from results of other aviation decision-making studies. The relationship between contingency planning support and information on regions clear of adverse weather was investigated in a scenario-based analysis. A rapid prototype example of the key elements in the depiction of icing conditions was developed in a case study, and the implications for the components of the icing information system were articulated.

One of the goals of designing engineering systems is to maximize the system's reliability. A reliable system must satisfy its functional requirements without failure throughout its intended lifecycle. The typical means to achieve a desirable level of reliability is through preventive maintenance of a system; however, this involves cost. A more fundamental approach to the problem is to maximize the system's reliability by preventing failures from occurring. A key question is to find mechanisms (and the means to implement them into a system) that will prevent its system range from going out of the design range. Functional periodicity is a means to achieve this goal. Three examples are discussed to illustrate the concept. In the new electrical connector design, it is the geometric functional periodicity provided by the woven wire structure. In the case of integrated manufacturing systems, it is the periodicity in scheduling of the robot motion.

This paper presents an Axiomatic Design framework for manufacturing system design and illustrates how lean cellular manufacturing can achieve volume flexibility. Axiomatic Design creates a design framework by mapping the functional requirements of a system to specific design parameters. Volume flexibility is often neglected as a requirement of manufacturing systems. Very few industries are fortunate enough to experience stable or predictable product demand. In reality, demand is often volatile and uncertain. It is important that manufacturing system designers are aware of manufacturing system types which can accommodate volume flexibility and follow a structured design methodology that assures that all requirements are met by the system.

A design framework based on the principles of lean manufacturing and axiomatic design was used as a guideline for designing an automotive component manufacturing system. A brief overview of this design decomposition is given to review its structure and usefulness. Examples are examined to demonstrate how this design framework was applied to the design of a gear manufacturing system. These examples demonstrate the impact that low-level design decisions can have on high-level system objectives and the need for a systems-thinking approach in manufacturing system design. Results are presented to show the estimated performance improvements resulting from the new system design.

This session keynote paper presents a framework for designing and deploying production systems. The framework enables the communication and determination of objectives and design solutions from the highest level to the lowest level of a manufacturing enterprise. The design methodology ensures that the physical implementation, called Design Parameters (DPs), meets the objectives or Functional Requirements (FRs) of the production system design. This paper presents a revolutionary approach to determine the objectives and the implementation of a “lean” production system design for a manufacturing business as guided by the design axiom of independence.

The linked cell system gives both reduced cost and volume flexibility. The characteristics of the linked cell system are a consequence of decoupling the operators from the machines, using standard work in process between the cells and by integrating the information system with the cell and system design. By decoupling the operators from the machines the capacity can be increased/decreased in small increments by using more or fewer operators in the cell. The information system is integrated with the linked cell design by the use of a Heijunka box. The Heijunka is used to level production and to initiate the pace of production as a result of pulling withdrawal kanban at a standard time interval. This standard time interval is called the pitch of production. The kanban cards give information about what to produce, when to produce, when to make changeovers but they also give information to control the material replenishment.

Lean production has greatly influenced the way manufacturing systems should be designed. One important aspect of lean production is takt time. Takt time relates customer demand to available production time and is used to pace the production. This paper applies the manufacturing system design and deployment framework to describe the impact of takt time on both the design and the operation of a manufacturing system. The goal of this paper is to illustrate the relevant relationships of takt time to overall system design.

With the recent advancement in sensing and controller technologies architecture design of an autonomous driving system becomes an important issue. Researchers have been developing different sensors and data processing technologies to solve the issues associated with fast processing, diverse weather, reliability, long distance recognition performance, etc. Necessary considerations of diverse traffic situations and safety factors of autonomous driving have also increased the complexity of embedded software as well as architecture of autonomous driving. In these circumstances, there are almost countless numbers of possible architecture designs. However, these design considerations have significant impacts on cost, controllability, and system reliability. Thus, it is crucial for the designers to make a challenging and critical design decision under several uncertainties during the conceptual design phase.