A model for evaluating alternative robot systems under uncertainty

Knott, Kenneth; Getto, Robert D.

doi:10.1080/00207548208947757

Cited by 47 publications

(7 citation statements)

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“…Arguably these models emphasize quantitative, financial analysis but fail to capture many of the 'intangible' benefits that should flow from AMT investments such as greater manufacturing flexibility, improved product quality and better employee morale (see for example, Abdel-Kader, 1997;Chen & Small, 1996;Dugdale & Jones, 1995;Accola, 1994;Cheung, 1993;Lavelle & Liggett, 1992;Naik & Chakravarty, 1992;Azzone et al, 1992;Rayburn, 1989;Park & Son, 1988;Srinivasan & Millen, 1986;Kaplan, 1986;ACARD, 1983;Knott & Getto, 1982).…”

Section: Introductionmentioning

confidence: 98%

Evaluating Investments in Advanced Manufacturing Technology: A Fuzzy Set Theory Approach

Abdel-Kader

Dugdale

2001

The British Accounting Review

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In this paper, a model for the evaluation of investments in advanced manufacturing technology is developed. Many authors have called for an integration of financial and non-financial factors in such evaluations, and this paper demonstrates that it is conceptually possible to do this using the mathematics of the analytic hierarchy process and fuzzy set theory. The development of the model has certain distinguishing features. First, it is based on a conceptual framework that combines the three dimensions of risk, financial return and non-financial factors. The empirical basis for this has been investigated and previously reported by the authors. Second, models previously developed and reported in the literature are shown to suffer from certain flaws relating to the use of linguistic scales, the ranking of fuzzy performance indicators and partiality in the treatment of investment decision variables. These issues are addressed through the development of simpler linguistic scales based on the analytic hierarchy, a revised procedure for ranking fuzzy numbers and an attempt to build a comprehensive model through the three dimensions described above. Triangular fuzzy numbers are used throughout in order to make the mathematics tractable and relatively easy to understand, and to facilitate presentation of a worked example. However, so that the reader is not misled, attention is drawn to some of the complexities in fuzzy arithmetic, especially the important distinction between subtraction/division and deconvolution of fuzzy numbers.

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Section: Introductionmentioning

confidence: 98%

Evaluating Investments in Advanced Manufacturing Technology: A Fuzzy Set Theory Approach

Abdel-Kader

Dugdale

2001

The British Accounting Review

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“…Sometimes, it is preferable to work directly with the alternatives, applying the normalization process using Equation (16). Furthermore, the ideal and anti-ideal solution alternatives must be normalized, according to Equations (17) and (18).…”

Section: Topsis Technique and Its Methodologymentioning

confidence: 99%

Agricultural Tractor Selection: A Hybrid and Multi-Attribute Approach

et al. 2016

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Usually, agricultural tractor investments are assessed using traditional economic techniques that only involve financial attributes, resulting in reductionist evaluations. However, tractors have qualitative and quantitative attributes that must be simultaneously integrated into the evaluation process. This article reports a hybrid and multi-attribute approach to assessing a set of agricultural tractors based on AHP-TOPSIS. To identify the attributes in the model, a survey including eighteen attributes was given to agricultural machinery salesmen and farmers for determining their importance. The list of attributes was presented to a decision group for a case of study, and their importance was estimated using AHP and integrated into the TOPSIS technique. In this case, one tractor was selected from a set of six alternatives, integrating six attributes in the model: initial cost, annual maintenance cost, liters of diesel per hour, safety of the operator, maintainability and after-sale customer service offered by the supplier. Based on the results obtained, the model can be considered easy to apply and to have good acceptance among farmers and salesmen, as there are no special software requirements for the application.

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“…Many precision-based robot selection methods are developed. Knott and Getto (1982) presented a model for robotics system evaluation considering uncertainty and considering labor components, net present values of cash flows of investment and overheads evaluated alternatives. Robot operations are simulated by Dooner (1983) in workspace and workspace is aided for robot selection.…”

Section: Introductionmentioning

confidence: 99%

Best–worst method for robot selection

Asif

Rashid

2020

Soft Comput

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For different applications, there are different robots having capabilities and specifications accordingly. For a particular application and industrial requirement, proper and suitable selection of robot is a difficult task. Numerous robot selection methods are available. Considering the research works on industrial robot selection, group best-worst method is employed in this paper for the proper selection of robots. Weighing the decision makers by considering their past experience is an important factor considered for expert and reliable selection of robot. Objective weights to describe the importance of the attributes along with the decision maker subjective preferences to describe the weights of the attribute are considered. Two problems are discussed for a detailed description and results are compared with the well-known group analytical hierarchy process method. The results show that due to lower minimum violation and lower total deviation, the proposed method performs better. Keywords Group best-worst method (G-BWM) Á Group analytic hierarchy process (G-AHP) Á Multiple attribute group decision making Á Subjective weights Á Objective weights Á integrated weights Communicated by V. Loia.

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A model for evaluating alternative robot systems under uncertainty

Cited by 47 publications

References 1 publication

Evaluating Investments in Advanced Manufacturing Technology: A Fuzzy Set Theory Approach

Evaluating Investments in Advanced Manufacturing Technology: A Fuzzy Set Theory Approach

Agricultural Tractor Selection: A Hybrid and Multi-Attribute Approach

Best–worst method for robot selection

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