Author supplied from the article: ABSTRACT Increasing global competition in manufacturing technology puts pressure on lead times for product design and production engineering. By the application of effective methods for systems engineering (engineering design), the development risks can be addressed in a structured manner to minimise chances of delay and guarantee timely market introduction. Concurrent design has proven to be effective in markets for high tech systems; the product and its manufacturing means are simultaneously developed starting at the product definition. Unfortunately, not many systems engineering methodologies do support development well in the early stage of the project where proof of concept is still under investigation. The number of practically applicable tools in this stage is even worse. Industry could use a systems engineering method that combines a structured risk approach, concurrent development, and especially enables application in the early stage of product and equipment design. The belief is that Axiomatic Design can provide with a solid foundation for this need. This paper proposes a ‘Constituent Roadmap of Product Design’, based on the axiomatic design methodology. It offers easy access to a broad range of users, experienced and inexperienced. First, it has the ability to evaluate if knowledge application to a design is relevant and complete. Secondly, it offers more detail within the satisfaction interval of the independence axiom. The constituent roadmap is based on recent work that discloses an analysis on information in axiomatic design. The analysis enables better differentiation on project progression in the conceptual stage of design. The constituent roadmap integrates axiomatic design and the methods that harmonise with it. Hence, it does not jeopardise the effectiveness of the methodology. An important feature is the check matrix, a low threshold interface that unlocks the methodology to a larger audience. (Source - PDF presented at ASME IMECE (International Mechanical Engineering Congress and Exposition
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from the article : To gain competitive power, product designs and their production means have become more and more complex over the past decennia. Product designers are faced with the increasingly difficult task to guarantee steady behavior of the systems they produce. This requires thorough understanding of the complex principles that determine the behavior of these products. It starts with notion how the many parts, of which the product design consists, are cross-linked with each other and their surroundings. If the design relations act predictable then the product design behaves predictable, and the functional requirements have high certainty of being satisfied. Axiomatic Design offers a number of ways to model the relations in a product design in order to improve its predictability. The ‘information content’ or ‘entropy’ of the design is indicative for the behavior of a system. The information content in Axiomatic Design is in the jurisdiction of the Information Axiom. This chapter investigates if information could be applied in a broader context; to bring the whole of methods in AD under a single heading. According to the definition of information by Shannon and Weaver, a broader application may be applied for Axiomatic Design. Along this path, an alternative framework of different kinds of information is decomposed that can be used to analyze progression in a product design. ‘Useful information,’ proportional to the ‘ignorance of the designer after application of all his knowledge,’ is decomposed into three kinds of information that are applied to graphically monitor the design process as it evolves.
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By applying Axiomatic Design, a Smart Medical Cast was developed to provide patients, who are suffering from forearm fractures, with a personalized healing process. The device monitors the overall healing status and three complications, which are: Muscle Atrophy, Compartment Syndrome, and Deep Vein Thrombosis. In the conceptual phase, desk research has been performed to find biomarkers that correlate with the monitored processes. Per biomarker, a measuring principle has been designed and these combined formed the design of the smart medical cast. Following the design phase, two tests were performed on healthy individuals to measure the robustness in a real application. The first test focused on correctly measuring the biomarkers and further specifying the sensor specifications. For the second test, a new prototype was used to determine correlations between the measured data and the monitored process and the impact of application during the casting process. The test results show that the measuring system can measure the biomarkers within the expected range, except for bone density. No significant impact on the casting process was measured. The Smart Medical Cast has only been evaluated in situations without a fracture, the next step will be to test the measurables in an environment with a fracture
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From the article: Abstract The Information Axiom in axiomatic design states that minimising information is always desirable. Information in design may be considered to be a form of chaos and therefore is unwanted. Chaos leads to a lack of regularities in the design and unregulated issues tend to behave stochastically. Obviously, it is hard to satisfy the FRs of a design when it behaves stochastically. Following a recently presented and somewhat broader categorization of information, it appears to cause the most complication when information moves from the unrecognised to the recognised. The paper investigates how unrecognised information may be found and if it is found, how it can be addressed. Best practices for these investigations are derived from the Cynefin methodology. The Axiomatic Maturity Diagram is applied to address unrecognised information and to investigate how order can be restored. Two cases are applied as examples to explain the vexatious behaviour of unrecognised information.
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From the article: "Axiomatic Design and Complexity Theory as described by Suh focus heavily on the coupling often found in functional requirements. This is so fundamental to the analysis of the design that it is the core of the Axiom of Independence which examines the coupling between functional requirements due to chosen design parameters. That said, the mapping between customer needs and functional requirements is often overlooked. In this paper we consider coupling, found due to this mapping, as a possible source of complexity in terms of a user interface to a designed product. We also re-examine the methodology of how customer needs are generated and translated into the other domains to understand how they can give further insight into the customer mindset. Based on this analysis, we believe customer domain complexity should always be examined in design that includes end-user interaction."
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From the article: Abstract Knowledge is essential to the product designer. It contributes to a better understanding of the difficulties in a design. With the right knowledge, design errors can be recognised in the early stage of product design, and appropriate measures can be applied before these errors escalate and delay the project. The axiomatic complexity theory, part of the Axiomatic Design methodology, can warn the designer in this process by disclosing his lack knowledge to fully understand the design. The Cynefin framework is a sense-making framework that distinguishes an organisational situation within four contexts. The state of relevant knowledge is the most important parameter to determine the actual context where an organisation, system, or design process is currently located. When knowledge is acquired, the context changes. Axiomatic Design and the Cynefin framework are applied in this paper to characterise the relation between the quality of the design and the knowledge of its designer. It is investigated if one follows the other, and how prompt that relation is. The outcome is that the quality of a design is proportional to the accumulation of applied knowledge to the product design. Therefore the quality of the design follows knowledge implementation but does not exceed the level of relevant knowledge of the designer. Knowledge should not be restricted to the designers only. Other people, e.g. production and maintenance-engineers, will also need the knowledge to take care of the product as the life cycle advances.
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from the article: ABSTRACT Independence of design, information and complexity are the basic concepts of Axiomatic Design. These basic concepts have proven to be generic; axiomatic design was successfully applied in many markets and on a broad range of products and services. Information, or entropy, plays a central role in Axiomatic Design. In this paper an attempt is made to organise the different kinds of information, understand them, and evaluate the consequences of the ways they can be applied. A number of six kinds of information are reduced to two most determining kinds of information for the design. Unorganised information is about choosing the right and independent design relations. Axiomatic information is about further optimisation of these design relations. This paper leads to the confirmation that axiom 1 & 2 are in fact corollaries of the complexity axiom that is constituted of the two kinds of information. Though this revises the foundation of Axiomatic Design, the operation and practical application are not much affected for a number of reasons. One of them is that a higher axiom does not alter the basic ideas behind Axiomatic Design; it remains axiomatic.
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From the article: The ‘Axiomatic Design Methodology’ uses ‘Axioms’ that cannot be proven nor derived from physical phenomena. The axioms serve as guidelines for the design process of products and systems. The latest contribution was the addition of the ‘Complexity Axiom’ in 1999. However, the underlying theory of complexity did not get much traction by designers and their managers yet. It emphasises difficulties in the design, not primarily focussing on solutions. The ‘Theory of Complexity’ is converted to a ‘Theory of Maturity’ in this paper. It is supported with a graphical way to plot maturity as it develops. It visualises the results in a way that can be understood by all entities in a company, engineers, managers, and executives. Understanding the maturity of a system enables selection of the right measures to control it. Visualisation enables communication between the interacting parties. If successful development trajectories are understood, eventually from earlier experience, even better corrective actions can be applied. The method appears an affirmative way to graphically represent progression in design, thus presenting advances in a positive context. Though positively presented, it is not the case that the method hides problems; presumed and legitimate project progression can be quite different, which challenges the designer to understand the process. In this way, the method sends out a continuous warning to stay critical on design choices made.
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Abstract Background: With the growing shortage of nurses, labor-saving technology has become more important. In health care practice, however, the fit with innovations is not easy. The aim of this study is to analyze the development of a mobile input device for electronic medical records (MEMR), a potentially labor-saving application supported by nurses, that failed to meet the needs of nurses after development. Method: In a case study, we used an axiomatic design framework as an evaluation tool to visualize the mismatches between customer needs and the design parameters of the MEMR, and trace these mismatches back to (preliminary) decisions in the development process. We applied a mixed-method research design that consisted of analyzing of 118 external and internal files and working documents, 29 interviews and shorter inquiries, a user test, and an observation of use. By factoring and grouping the findings, we analyzed the relevant categories of mismatches. Results: The involvement of nurses during the development was extensive, but not all feedback was, or could not be, used effectively to improve the MEMR. The mismatches with the most impact were found to be: (1) suboptimal supportive technology, (2) limited functionality of the app and input device, and (3) disruption of nurses’ workflow. Most mismatches were known by the IT department when the MEMR was offered to the units as a product. Development of the MEMR came to a halt because of limited use. Conclusion: Choices for design parameters, made during the development of labor-saving technology for nurses, may conflict with the customer needs of nurses. Even though the causes of mismatches were mentioned by the IT department, the nurse managers acquired the MEMR based on the idea behind the app. The effects of the chosen design parameters should not only be compared to the customer needs, but also be assessed with nurses and nurse managers for the expected effect on the workflow.
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