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    Designing robust capability-based distributed machine layouts with random machine availability and fuzzy demand/process flow information
    (Springer Science and Business Media LLC, 2023) Subulan, Kemal; Varol, Bilge; Baykasoğlu, Adil
    Thus far in the available literature, capability-based distributed layout (CBDL) design approaches were only developed under certain environments. Indeed, uncertainties embedded in the machine unavailability (or random machine breakdowns), product demands, and process flow data were not considered by the previous studies to achieve a robust CBDL design. However, many real-life facility layout design applications may involve different types of uncertainties simultaneously, like fuzziness and stochasticity. Based on this motivation, for the first time in the literature, this paper introduces a novel robust capability-based distributed layout (R-CBDL) design problem under a mixed fuzzy-stochastic environment. First, a new fuzzy-stochastic optimization model of the R-CBDL design problem is developed by considering the random machine breakdowns and fuzzy demand/process flow data. Then, a hybrid solution approach based on a chance-constrained stochastic programming technique with a well-known interactive fuzzy resolution method is proposed. Thus, the random machine breakdowns and fuzzy part flow rates among different machining capabilities could be easily handled via the proposed approach. Fortunately, the proposed approach can also generate various risky and risk-free robust layout design alternatives under different probabilistic scenarios and uncertainty levels (a-cuts) according to the facility designer’s risk attitude. To show the validity and applicability of the proposed R-CBDL problem and hybrid solution approach, an extensive computational study with comparative analysis is first presented based on an illustrative numerical example under different machine capability overlap cases and probability distributions. Then, the performance of the proposed approach is also tested on a real-life cellular manufacturing system of a company. The computational experiments have shown that the proposed approach can accomplish more efficient robust layout design alternatives with on average 24.5% better total expected layout score when compared to the existing cellular layout of the manufacturing company.
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    Unequal-area capability-based facility layout design problem with a heuristic decomposition-based iterative mathematical programming approach
    (Elsevier, 2023) Varol, Bilge; Subulan, Kemal; Baykasoğlu, Adil
    Thus far in the available literature, capability-based facility layout design approaches were developed by only considering equal machine areas, where they are assigned to the pre-specified locations. Based on this motivation, this paper introduces a new unequal-area capability-based facility layout design (UA-CBFLD) problem for the first time in the literature. In addition to the machines’ unequal-area requirements, the proper distribution of their processing capabilities over the shop floor is considered. First, a new mixed-integer non-linear programming (MINLP) model is developed. Then, a polyhedral inner-approximation method is applied to cope with nonlinear area constraints. Due to its NP-hard nature and highly non-linear structure, a heuristic decompositionbased iterative solution approach is also proposed to solve realistic size problems within a reasonable time. In order to show the validity and applicability of the proposed approach, both an illustrative example with different machine-capability overlaps and a real-life application in a manufacturing company are presented. The computational results have shown that the proposed approach has found a 33.25% better layout score (as a function of the distance and the amounts of product flows) and achieved this solution 116.64% faster than the solution of the developed MINLP model via Gurobi’s standard non-linear programming solver. Furthermore, when compared to the existing cellular facility layout design of the manufacturing company, the proposed capability-based unequal-area layout design option has also 29.37% and 34.74% superior layout scores under the scenarios of equal and unequal machine areas, respectively. Moreover, the total average machine utilization has increased up to 89.6%, which is comparatively better than the current average cell utilization, i.e., 65.2%.