A Virtual Cellular Manufacturing System Design Model Based on Axiomatic Design Theory

2012 ◽  
Vol 271-272 ◽  
pp. 1478-1484 ◽  
Author(s):  
Wen Min Han ◽  
Jin Lei Zhao ◽  
Ying Chen
Keyword(s):  
Design Theory ◽  
Manufacturing System ◽  
Cellular Manufacturing ◽  
Axiomatic Design ◽  
Virtual Manufacturing ◽  
Cellular Manufacturing System ◽  
System Cost ◽  
Virtual Cell ◽  
Model Based ◽  
Axiomatic Design Theory

This paper presents a virtual cellular manufacturing system building model based on axiomatic design theory. By now most discussions of virtual manufacturing cellular focus on how to format a virtual cell and how to optimize a virtual cell in the execution layer. The attention to “system cost” and “efficiency” mostly were given only after the system-generated. In this paper we build a complete virtual cellular manufacturing system, and pay attention to “system cost” and “efficiency” in the conceptual design phase to make sure the techniques and resource which we choose is low-cost and non-redundant. Meanwhile in Process Domain of the model, we blend the logistics balance idea of TOC theory, waste elimination philosophy of lean manufacturing and the existing conclusions of the virtual cell literature to make sure the tools which we choose are more effective. The model will clearly set out the concept, principle and technology hierarchy of virtual cellular manufacturing system, and can be an effective map for manufacturing enterprises with low-volume and high-variety to apply the virtual cellular production.

Aspects on Process Planning Issues in Axiomatic Design

1994 ◽  
Author(s):  
Johan Vallhagen
Keyword(s):  
Design Theory ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Axiomatic Design ◽  
Original Method ◽  
Design Parameters ◽  
Complex Products ◽  
Additional Process ◽  
Axiomatic Design Theory ◽  
Complex Manufacturing Systems

Abstract This paper addresses some limitations of the axiomatic design theory (AD) when designing complex products and matching manufacturing systems. The conclusion is that, for complex manufacturing systems, this cannot be done in such a straightforward way as described in literature. The original method is best used for manufacturing of parts only, i.e. to find the appropriate process variables (PVs). In the case of complex manufacturing systems, a one-to-one mapping between physical domain and process domain is not possible since not all design parameters (DP) are components. Therefore, an additional process requirement domain (PR), proposed earlier, has been used. With it, the components are extracted from the DP hierarchy and mapped to different spaces in the manufacturing world. In these spaces, PRs and PVs are selected when designing the manufacturing system. An example is given to show the deficiencies and how to use the suggested modifications.

scholarly journals Axiomatic Design: 30 Years After

2015 ◽  
Author(s):  
Mats Nordlund ◽  
Taesik Lee ◽  
Sang-Gook Kim
Keyword(s):  
Design Process ◽  
Design Theory ◽  
Organizational Design ◽  
Design Research ◽  
Design Thinking ◽  
Axiomatic Design ◽  
Environment Design ◽  
Good Design ◽  
Axiomatic Design Theory ◽  
Practical Experiences

In 1977, Nam P Suh proposed a different approach to design research. Suh’s approach was different in that it introduced the notions of domains and layers in a 2-D design thinking and stipulated a set of axioms that describes what is a good design. Following Suh’s 2-D reasoning structure in a zigzagging manner and applying these axioms through the design process should enable the designer to arrive at a good design. In this paper, we present our own experiences in applying Suh’s theories to software design, product design, organizational design, process design, and more in both academic and industrial settings. We also share our experience from teaching the Axiomatic Design theory to students at universities and engineers in industry, and draw conclusions on how best to teach and use this approach, and what results one can expect. The merits of the design axioms are discussed based on the practical experiences that the authors have had in their application. The process developed around the axioms to derive maximum value (solution neutral environment, design domains, what-how relationship, zig-zag process, decomposition, and design matrices) is also discussed and some updates are proposed.

scholarly journals Facility layout for cellular manufacturing system under dynamic conditions

2016 ◽  
pp. 407-416 ◽  
Author(s):  
Amir-Mohammad Golmohammadi ◽  
Hamid Bani-Asadi ◽  
Hamid Esmaeeli ◽  
Hengameh Hadian ◽  
Farzaneh Bagheri
Keyword(s):  
Manufacturing System ◽  
Cellular Manufacturing ◽  
Facility Layout ◽  
Cellular Manufacturing System ◽  
Dynamic Conditions

Application and limitation of axiomatic design complexity in quality engineering

2015 ◽  
Vol 32 (1) ◽  
pp. 3-17
Author(s):  
Naresh K. Sharma ◽  
Elizabeth A. Cudney
Keyword(s):  
Normal Distribution ◽  
Uniform Distribution ◽  
Design Theory ◽  
Bounded Solution ◽  
Current Method ◽  
Axiomatic Design ◽  
Complexity Measure ◽  
Specification Limits ◽  
Content Type ◽  
Axiomatic Design Theory

Purpose – Complexity is an important element in axiomatic design theory. The current method for calculating complexity for a system following normal distribution is unbounded and approximate. The purpose of this paper is to present a detailed bounded solution for complexity using design and system ranges on a single function requirement. Design/methodology/approach – This paper discusses the complexity measure for a system following a uniform distribution. The complexities of two types of systems, a system performing with a uniform distribution and a system performing on target according to a normal distribution are then considered and compared. The research proposes a complexity measure for a system performing within specification limits with a uniform distribution. In addition, a new concept of relative complexity is proposed. Findings – A bounded solution for complexity for a normal distribution based on the existing assumptions was given which includes bias in addition to variance. The bounded solution was then compared to the existing approximate solution from the variance as well as bias standpoint. It was found that bias has an inappropriately reverse relationship with the bounded solution of complexity. Therefore, complexity cannot be used to approximate the system improvement when the improvement is based on a reduction in bias. Originality/value – The current method for calculating complexity for a system following normal distribution is unbounded and approximate. This paper proposed a complexity measure for a system performing within specification limits with a uniform distribution.

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