A hierarchical fuzzy axiomatic design methodology for ergonomic compatibility evaluation of advanced manufacturing technology

Maldonado, Aide; García, Jorge Luis; Alvarado, Alejandro; Balderrama, Cesar Omar

doi:10.1007/s00170-012-4316-8

Cited by 45 publications

(19 citation statements)

References 31 publications

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“…Modern digital HMI has numerous characteristics, such as information complexity (Yockey 2002), structure complexity (Zhang 2012), task complexity (Liu and Li 2012) and complex environment (Maldonado et al 2013). Operators must control a variety of devices in a specific manufacturing environment.…”

Section: Introductionmentioning

confidence: 99%

Influence of information overload on operator’s user experience of human–machine interface in LED manufacturing systems

Zhu

Cao

et al. 2015

Cogn Tech Work

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This paper reports on an experimental study on human-machine interface in LED manufacturing systems to measure the influence of information overload on user experience. The results are based on cognitive ergonomics. The experiment used eye-tracking methods and a questionnaire to gather data. The independent variables were interface complexity and user background. Interface complexity had three levels: high interface complexity, moderate interface complexity and low interface complexity. User background had two levels: the novice group and the expert group. The dependent variables included time to first fixation, fixations before and subjective feelings. A total of 38 operators participated in the experiment, and the results showed that (1) interface complexity caused a significant difference in time to first fixation (P \ 0.05) and fixations before (P \ 0.05). Furthermore, the results revealed significant differences between high complexity interfaces compared to low complexity interfaces (P \ 0.05). However, no significant differences were observed between moderate and low complexity interfaces or between moderate and high complexity interfaces (P [ 0.05); (2) user background significantly affected the user experience; (3) within the same complexity level, expert operators' cognitive workload was significantly lower than that of novice operators; and (4) there was no significant relationship between the interface complexity and the user's background. The study concludes that because interface complexity has a significant effect on the time taken to locate the target button on the screen, interface design should be as simple as possible, while still providing the necessary level of functionality.

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Section: Introductionmentioning

confidence: 99%

Influence of information overload on operator’s user experience of human–machine interface in LED manufacturing systems

Zhu

Cao

et al. 2015

Cogn Tech Work

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“…For this, the Theory of Axiomatic Design extended by , Helander and Lin (2002) and adopted by Karwowski (2001 was also evolved. For this approach a Hierarchical Fuzzy Axiomatic Design Survey for Compatibility Evaluation of AMT was designed based on a pragmatic perspective and a large amount of literature that was reviewed and presented in Maldonado et al (2009), Maldonado et al (2013). This evaluation approach can be adapted to be immersed into a Lean-Six Sigma framework.…”

Section: Fuzzy Axiomatic Design Methodologymentioning

confidence: 99%

Lean Manufacturing in the Developing World

Alcaráz¹,

Maldonado-Macías²,

Cortés-Robles³

2014

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“…The design goals, i.e. DR for the seven criteria are decided while using a five point linguistic scale set as least poor (LP), least fair (LF), least good (LG), least very good (LVG) and least excellent (LE) with their corresponding TFNs as (0,10,10), (2,10,10), (4,10,10), (6,10,10) and (8,10,10) respectively (Maldonado et al 2013). The selection committee has unanimously deci ded on the DRs of the seven criteria of strategic skills (C 1 ), process management skills (C 2 ), team skills (C 3 ), decision making skills (C 4 ), behavioural skills (C 5 ), negotiation skills (C 6 ) and quantitative skills (C 7 ) as LE, LE, LG, LE, LG, LVG and LVG respectively.…”

Section: Illustrative Problemmentioning

confidence: 99%

Personnel Selection Using Fuzzy Axiomatic Design Principles

Khandekar

Chakraborty

2016

Business: Theory and Practice

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Overall competency of the working personnel is often observed to ultimately affect the productivity of an organization. The globalised competitive atmosphere coupled with technological improvements demands for efficient and specialized manpower for the industrial operations. A set of typical technological skills and attitudes is thus demanded for every job profile. Most often, these skills and attitudes are expressed imprecisely and hence, necessitating the support of fuzzy sets for their effective understanding and further processing. In this paper, a method based on fuzzy axiomatic design principles is applied for solving the personnel selection problems. Selecting a middle management staff of a service department for a large scale organization is demonstrated here as a real life example. Five shortlisted candidates are assessed with respect to a set of 18 evaluation criteria, and the selection committee with experts from the related fields also realizes the outcome of the adopted approach to be quite appropriate, befitting and in agreement with their expectations.

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A hierarchical fuzzy axiomatic design methodology for ergonomic compatibility evaluation of advanced manufacturing technology

Cited by 45 publications

References 31 publications

Influence of information overload on operator’s user experience of human–machine interface in LED manufacturing systems

Influence of information overload on operator’s user experience of human–machine interface in LED manufacturing systems

Lean Manufacturing in the Developing World

Personnel Selection Using Fuzzy Axiomatic Design Principles

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