Multi-criteria Decision-Making Approaches for Facility Layout (FL) Evaluation and Selection: A Survey

Besbes, Mariem; Affonso, Roberta Costa; Zolghadri, Marc; Masmoudi, Faouzi; Haddar, Mohamed

doi:10.1007/978-3-319-66697-6_59

Cited by 6 publications

(7 citation statements)

References 29 publications

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“…If an engineer shows an output with quantitative metrics, this information may be information overload or appear inaccurate to the decision maker. This may be because many of the current methods reviewed by Besbes et al (2019) have no associated visual or quantitative metrics displayed in conventional units. The methods which do provide any form of metrics often elect to use non-conventional units such as an arbitrary scale or a low, medium, and high rating system-often difficult to interpret or to use for comparisons without an extended explanation by the creator of the scaling system.…”

Section: Belief For Rejection Of Current Academia Methodsmentioning

confidence: 99%

“…o Expansion flexibilitythe capability for a facility to adjust to additional capacity with ease. Typical characteristics include large amounts of floor space with, "good shape factors or useable areas" (Besbes et al, 2019).…”

Section: Qualitativementioning

confidence: 99%

“…o Volume flexibilitythe capability for a facility to adjust to large increases or decreases to scheduled production amounts. Changing the number of manufacturing facilities can change this metric (Besbes et al, 2019).…”

Section: Qualitativementioning

confidence: 99%

“…Many of these methods utilize an automated technique for comparing layouts but require human measurement and input of data from metrics. These methods were introduced in the order: GRA (Kuo, Yang, & Huang, 2006), TOPSIS and fuzzy TOPSIS (Yang & Hung, 2007), a second GRA (Kuo, Yang & Huang, 2008), ELECTRE (Lateef-Ur-Rehman, Ateekh-Ur-Rehman, & Babu, 2009), PROMETHEE (Rehman & Rehman, 2012), PSI (Maniya & Bhatt, 2011), a simulation, fuzzy analytic hierarchy process, and quality function deployment (Shahin & Poormostafa, 2011), a second TOPSIS and fuzzy TOPSIS (Ataei, 2013), MACBETH (Karande & Chakraborty, 2014, followed by aggregating survey results for previous methods (Besbes et al, 2019).…”

Section: Automated Techniquesmentioning

confidence: 99%

“…The result was that the industry expert accepted the technique as superior. Besbes et al (2019) noted in their discussion and conclusion section, "In fact, the commercial software available to reinforce the facility layout problems are currently restricted." (Besbes et al, 2019).…”

Section: How Can Warehouse Layout Designs Be Compared Better?mentioning

confidence: 99%

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Demonstration of the value of a graphics-based decision support system for order picking warehouse design

Kryk¹

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All warehouses have a layout design. A company can reduce operational costs in their warehouse by up to 75% with a layout design that allows for products on a pick list to get picked quicker. Evaluating which layout design would best reduce picking times and communicating the results of that evaluation continue to stump workforces.Manual techniques fail to quickly test layout designs en masse or offer inaccurate heuristics. Automated techniques often increase the accuracy but are either esoteric or have simulation run-times which rival the durations of a manual technique.A fast and accurate automated technique that is both executable and provides quantitative and visual outputs accessible to a layperson was documented and empirically tested against a manual technique of similar stature. Time studies were conducted to measure and compare the process times for analyzing different layout design alternatives with both techniques, using data provided by a retailer for analysis.The proposed automated technique had a process time of 12 minutes to produce the outputs for each subsequent layout design iteration while the manual technique provided identical outputs at a process time of 16.5 hours per iteration.The value of these outputs and this technique was confirmed by an industry expert and students in the Industrial and Manufacturing Systems Engineering program at Iowa State University.With the implementation of this automated technique, industry can expect accuracy, picking output data accessible to laypeople, layout visuals illustrating optimal routing, data for determining staffing levels under different demands, and the ability to test multiple layout xii designs-all by a worker with minimal training. The outputs are expected to lead to better decision making when choosing a layout design alternative as a team.

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Section: Belief For Rejection Of Current Academia Methodsmentioning

confidence: 99%

Section: Qualitativementioning

confidence: 99%

Section: Qualitativementioning

confidence: 99%