Systematic design methodologies for a technical system development examine the functions that are required to transform an operand from its current stage to the desired
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stage. Within a generic new product development, the methods and various creative and systematic techniques are introduced to generate solutions (Hubka & Eder 1982, Pahl &
Beitz 1996). These methods approach the development task from “scratch”, meaning that no previous solution is utilized as a starting point.
Concept development is based on the break-down of the functional structure, for which the solution alternatives are explored. Further on, as alternative solutions have been identified, different combinations of sub-functions are evaluated for the realization of the required overall function or behaviour [Figure 5.6] (Pahl & Beitz 1996).
Figure 5.6 Functional structure broken down as black box sub-functions and classification scheme to organize solution alternatives towards Morphological graph to combine concepts. Adopted from Pahl & Beitz (1996).
As noted before, a typical industrial development project originates from other drivers, typically the need for performance improvements and/or cost pressure. Concept development based on existing solutions and the search for better alternatives are essential for maintaining the competitiveness of products. Like any development activity, concept development begins with an analysis of the current state and then evaluates how product functions and properties are built into the technical system, how the functional structure is built and how relations between sub-functions and system modules interact. The various techniques, which may be applied in search of product improvements and as a basis for concept development, are presented:
QFD
Quality Function Deployment (QFD) provides a methodology for assessing how product properties can be interpreted as measuring design parameters. When fully utilized, QFD provides a comprehensive matrix that can compare and judge the importance of different product properties, different solutions and benchmark against competing products
The utilization of QFD provides a systematic tool for developing product quality by identifying properties which are either in contrast with the requirements or in conflict with another property. The methodology provides a measurable means to understand customer requirements and maximize those positive qualities that add value [Figure 5.7] (Akao 1990).
61 Figure 5.7 QFD, the elements of the house of quality showing the principles how
design requirements and their impact on a design concept is evaluated.
Adopted from Akao (1990).
However, as QFD aims to provide explicit measures for a designer, the principle of the defining product into properties which can be characterized with one or few design parameters is challenging. For instance, how can interactions between functions and properties be considered? QFD has a similarity with the axiomatic design principle, in which the isolation of design parameters aims for robust and stable design (Suh 1990).
With QFD, once the product and its most important properties are separated and their parameters set, the importance of the evaluation guides subsequent development actions.
The weakness of the tool is similar to all numerical assessment methods in that the results reflect the opinions and preferences of the one who made the selection of the grading and weighting of each property. As it has been widely applied over decades, QFD has great advantages for comparing properties and identifying potential development issues, its utilization for generating or developing alternative solutions is poor.
Dependency matrices (DSM)
Interactions and impacts modelling method, Design or Dependency Structure Matrix (DSM) in various forms originates back to the 1960s (Steward 1981). Due to a wider attention given to the design process-modelling arena, the DSM-method was developed through research at the Massachuset Institute of Technology. (McCord & Eppinger 1993, Pimmler & Eppinger 1995).
The origin of DSM was based on the graphical modelling of a system with elements, which are assumed to completely describe a system and characterize its behaviour. The elements are connected with nodes to present relationships between them. The directionality of influence is shown by an arrow, in comparison to a simple link which is shown without arrows. The later format of the dependency between elements in a matrix representation becomes binary, and in the matrix layout the system elements names are placed down the side of the matrix as row headings and across the top as column headings in the same order. If there exists a relationship from one element to another, the value of the crossing element is 1 (or x), otherwise zero (or empty) [Figure 5.8].
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Figure 5.8 Presentations of Design Structure Graph and Design Structure Matrix visualizing the relationship between system elements. Adopted and modified from DSMweb (2009).
Binary DSM-matrices can represent the presence or absence of a dependency between pairs of elements in a system and the ability to provide a more systematic mapping through the organization or grouping of system elements. Various applications, examples and further developments of DSM matrices have been presented widely in the literature.
While the development and application of matrices has expanded, the context has also changed; the dependencies are no longer directional, e.g. the structure of the product is considered static and the relevance of which elements are important to each other can be determined (Lehtonen 2007).
Malmqvist (2002) recognizes different methods of analysis with dependency structure matrices, i.e. clustering, partitioning coverage, index computation, interaction, change propagation and alignment, of which the latter three may be more applicable to concept development as they focus on the element relations and effects of change.
However, although the application of matrix methods is rather easy and their advantage, especially with element clustering is clear, the problem of what relations should be examined and how the results may be applied to concept development is ambiguous. This is addressed as the concept development takes place at an early stage of development, and thus the analysis of detailed elements enlarges the matrix presentations beyond a practical size. That also occurs with the Multiple Domain Matrix presentation when it aims to define several domains or disciplines.
Function Analysis System Techniques (FAST)
The design strategies approach the exploration of requirements fulfilment through the functional view. Accordingly, the concept modelling and analysis method that uses that viewpoint is found in literature. Already in the 1960s Bythaway (2005) introduced one of the first analysis methods, Function Analysis System Technique Diagram (FAST). The first applications were used for Value Engineering, but were proposed as being also successful for Engineering Design or any systematic design strategy. The systematic design strategy establishes a functional structure from the input-output nature and should be solution neutral. The FAST diagram aims to prioritize the objectives or functions of a product, it is possible to evaluate from the options which would return the most value based or predetermined value, namely;
• Targeting true customer needs and wants.
• Delivering requirements but still enabling cost reduction by focusing on “what the function accomplishes” versus “what the product is”.
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• The elimination of unimportant requirements.
• Adding incremental costs to achieve a larger performance benefit.
• Improving performance and reducing cost simultaneously.
The difference between FAST and functional decomposition is the two opposite approaches; as the functional decomposition from the left builds on how the functions will be accomplished, the approach from right asks why the function exists [Figure 5.9].
Figure 5.9 The two approaches of FAST diagram on functional decomposition, how and why the functions are designed and distinction to primary (FP) and supporting (FS) functions. Adopted and modified from Bytheway (2005).
As the functional presentation includes essential basic and secondary supporting functions, the elimination of unnecessary functions is recognised through the primary function path and questioned from the right hand approach.
The FAST-technique approach is linear and as it breaks down function into smaller secondary functions it has a similarity with axiomatic design [Figure 5.10].
Figure 5.10 The representation of functional requirements (FR) and design parameter hierarchies (DP) where the first layer (overall function) is not uncoupled but next are. Adopted from Suh (2001).
FAST aims to eliminate unimportant requirements and search for better alternative solutions; in contrast the goal of the axiomatic design is to uncouple design elements by breaking function into pieces or modules where the function is affected only by one design parameter (Suh 2001).
However, even though both methods systematically split total function into smaller sub- functions, and simplify and limit the complexity of one particular design task, their support for developing concepts is poor. The methods for the identification of opportunity and
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what needs to be developed do exist, but further development is needed for the methods to be applied.