International Journal of Industrial Engineering: Theory, Applications and Practice
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DEVELOPMENT OF A DATA-DRIVEN SMART PRODUCT SERVICE SYSTEM FRAMEWORK UTILIZING UNSUPERVISED LEARNING MODEL
No full textMany studies have addressed traditional product-service system (PSS) design, but a combination of data-oriented PSS with emerging technologies to achieve a Smart PSS that can respond to a continuously changing environment remains absent. Therefore, this study proposes a systematic framework that utilizes text analytic techniques to capture PSS via a data-oriented service blueprint for use in identifying improvement opportunities and proposes an improvement plan merging a PSS design process and Bidirectional Encoder Representations from Transformers (BERT), which can handle context-sensitive services with smart and connected products in a dynamic environment. By utilizing a data-driven service blueprint and unsurprised learning model, a Smart PSS is transformed. Experiment shows this tourism recommendation generates enhanced service quality and customer satisfaction
EVOLUTION OF 2K FACTORIAL DESIGN: EXPANSION AND CONTRACTION OF THE EXPERIMENTAL REGION WITH A FOCUS ON FUZZY LEVELS
No full textThis research presents a novel approach of an evolution of the 2k factorial design (E2kFD) which is based on a fuzzy search heuristic technique. Moreover, this approach allows multiple horizontal and vertical exploration spaces, expanding and contracting the experimental region within the region of operability. It can be achieved by defining a variable position for each point or treatment of study factors in its geometric representation, as an alternative to the conventional 2k factorial design in which fixed positions at the vertices of its geometric representations are defined. In general, the main disadvantage of model-based DoE methods is the requirement for fast and reliable decision making in setting the deterministic value for each level. It is often that the value of the levels is unknown in advance inducing imprecision and vagueness when these are determined by experts based on their heuristic knowledge. For this reason, the proposed method combines the main advantages to use values with uncertainty for each one of the levels and to be able to explore inside and outside of the experimental region to assign variables positions to coded levels, and therefore the method works iteratively. Moreover, in the proposed fuzzy search heuristic technique approach the high and low levels of each factor are considered as linguistic variables. These are classified into three linguistic labels in a simple and clear language as: regular, major and minor which are used as an indicator of strength. A maximum fuzzy operator in the implication and aggregation stages are used to search the highest membership value and their position to assign feasible fuzzy levels as one of the scientific contributions of the present investigation. The method is demonstrated with a simulation, which shows the potential of the proposed approach. Additionally, the traditional 2k factorial and our evolved E2kFD expert designs were validated conducting the experimental tests in a textile company in southern Guanajuato, Mexico. Finally, by comparing the results between the traditional and our proposed designs, it will be shown that better explanation and prediction models for the response variables under study are obtained with the E2kFD proposed design
AN EXPLORATORY ASSESSMENT OF THE SUSTAINABILITY PERFORMANCE OF THE CONSTRUCTION INDUSTRY
No full textThis research aims to evaluate the sustainability performance of six India-based construction organizations by considering the triple bottom line approach to sustainability (environmental, social, and economic). First, the significant parameters for evaluating performance are identified from an extensive literature review. Second, data are collected by developing a questionnaire and carrying out a survey with selected industry experts. Subsequently, an integrated framework is developed in which item analysis examines the consistency of the data, principal component analysis determines the criteria weights, and a simple additive weighting method ranks organizations according to their performance scores. Finally, the benchmark organization is identified and its strategy has been explored. Additionally, the critical parameters in each stage of the construction supply chain are identified using the weighted mean method. The results reveal that ‘Capital Budgeting’, ‘Lifecycle Design’, ‘Use of Energy-Efficient Technology’, and ‘Cost of Waste Disposal’ are the most influential parameters in the inception, design and planning, construction and maintenance, and demolition and reverse logistics stages, respectively
WASPAS METHOD FOR CORRELATED RESPONSE OPTIMIZATION DURING DRILLING OF NANO ONIONS STRUCTURED CARBON-REINFORCED POLYMER COMPOSITES
No full textThis study investigates the machinability aspects and parametric optimization during the drilling of Carbon nano onion reinforced polymer (epoxy) nanocomposites. A hybrid module of Principal Component Analysis (PCA) and Weighted Aggregated Sum Product Assessment (WASPAS) technique is explored to achieve the desired machining responses. The proposed module efficiently optimizes the four process parameters, namely, CNO % (Wt.%), Speed (S), Feed (F), and Drill-bit materials (M) (HSS, Carbide, and TiAlN). The study aims to determine the optimum value of the three process responses, i.e., Torque (Tr), Thrust force (Tf), and Surface roughness (Ra), in terms of a single objective function value (Qi). ANOVA is utilized to determine the percentage contribution of each drilling variable. The optimum settings were obtained at CNO Wt.% - 0.5 %, S-1500 rpm, and F-100 mm/min with a TiAlN drill bit. The findings of the hybrid PCA-WASPAS are more feasible (11.596 %) than the conventional WASPAS method
INTEGRATED MODEL BASED ON EXTENDED FUZZY AHP AND CRITICALITY ANALYSIS FOR RISK ASSESSMENT IN CUSTOMS SUPPLY CHAIN: A PERSPECTIVE FROM MOROCCO
No full textThe purpose of the current study is to assess risk in the customs supply chain. A risk assessment model using a combination of the extended fuzzy (EF) analytic hierarchy process (AHP) method with criticality analysis is proposed. EFAHP may be used as an efficient method for determining the importance of risks in the assessment process, but it does not determine whether the risks are at an acceptable level based on their risk points. A risk assessment study was conducted on Moroccan customs, in which threats were determined based on experience. The past 10 years’ statistical records were categorized, and each category was prioritized using the EFAHP method. EFAHP is a useful tool that considers the fuzziness of the data involved in determining the preferences for various decision variables. The fuzzy set theory gives a much better representation of the subjective judgments. Thus, it further refines the evaluation problem. The determined risks were also assessed based on criticality. The relation between the assessment of the risk class based on criticality and the fuzzy AHP weights was examined, and the risk class intervals for EFAHP were determined. In the study, an approach was developed based on the fact that the measure of the risk class in criticality risk assessment can be used with the obtained results, using the EFAHP method by comparing the obtained priority weights against the normalized scores of criticality. Therefore, the importance and classes of risks are determined
A two-echelon supply chain model with time-varying selling price and demand rate
No full textPrices of hi-tech products usually decline with the passage of time because of rapid technical modernization and universal competitiveness as well as high servicing and maintenance cost after products being sold. In this paper, we develop a two-echelon supply chain model wherein a manufacturer supplies a single high-tech product to a retailer under lot-for-lot policy. The retail price of the product is assumed to be a sum of basic price which is taken as a retail fixed markup (RFM) over the manufacturer’s wholesale price and a variable price which is inversely related to the servicing and maintenance cost. Assuming that the retailer’s demand rate is dependent on the retail price, we develop integrated as well as decentralized models with continuous and discrete time selling prices. For numerical examples, we illustrate the developed models and examine the sensitivity of model-parameters
A ROBUST POSSIBILISTIC APPROACH FOR MULTI-DEPOT INVENTORY ROUTING PROBLEM
No full textThis study proposes a robust model for the inventory-routing problem in which a set of suppliers distribute some products to multiple customers facing uncertain demands over a finite time horizon. Customers' demand has not a specified probability distribution. The only knowledge about the demand of customers is that these uncertain parameters are random variables and can take any value in their determined interval. The suppliers are taking into account for managing the inventory of their customers. Each customer can be allocated to any supplier at any period. The proposed model is to determine the amount of each product that must be delivered to each customer as well as the route and the time. To cope with this type of uncertainty, a robust-possibilistic method is applied in the context of the inventory-routing problem. The efficiency of the proposed model is demonstrated by numerical experiments and some sensitivity analyses
Risk Assessment in Oil and Gas Industry Using Simulation and Bow-Tie Analysis
No full textRisks have been in the forefront of supply chain management because of the exponential rise of natural disasters and the noticeable increase of supply chain disruptions. In oil and gas industry, risk events can be associated with consequences that might lead to fatalities and loss of millions of dollars. Therefore, effective risk management is vital for oil and gas companies. In this research, a framework that combines simulation and Bow-Tie risk modeling is proposed to study the disruption risks in oil and gas supply chains. The simulation model captures the flow of material and information and accounts for the dynamic interactions among the system components. Bow-Tie analysis is used to quantify the risks and their impact. A case study is provided to demonstrate the application of the proposed framework and to show its effectiveness as a decision-support tool that can be used in disruption risk management
Analysis for waste collection and management of closed-loop supply chain with dual-channel forward logistics
No full textThis paper focuses on the optimal pricing and collection rate decision for a dual-channel forward supply chain, with which the manufacturer sells products via direct channel and retail channel in the forward logistics, while the recycling competition between manufacturer and retailer exists in reverse logistics with waste. Based on game theory, we characterize the profit functions of manufacturer and retailer in closed-loop supply chain with the different scenarios of reverse logistics. By comparison the different scenario, we provide some suggestion for the manufacturer’s and retailer’s pricing and collection rate policies
Mathematical Approximation of Single and Double-Sided Truncated Normal Distribution Using Logistic Function
No full textThis article provides a mathematical approximation model of the general double-sided truncated normal distribution. The right and left-sided cases are included in the model as special cases. The double-sided truncated normal distribution is important for many applications in industrial and systems engineering. For example, in quality control, production engineers maybe interested in scrapping the unfit products. The distribution of product variations after this scrapping is basically double-sided truncated normal distribution. A full analysis of deviation of the introduced approximation’s results from the actual results is provided. Further, recommendations for the use of the model are provided