A multicriteria framework for inventory classification and control with application to intermittent demand

Lolli, Francesco; Ishizaka, Alessio; Gamberini, Rita; Rimini, Bianca

doi:10.1002/mcda.1620

Cited by 15 publications

(12 citation statements)

References 44 publications

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“…Among them, the most commonly used [15] is certainly the Analytic Hierarchy Process (AHP), originally developed by Saaty [16], which calculates criteria priority vectors and rank alternatives. AHP can be applied to virtually any field, such as water supply [17] and environment management [18], among many others. Moreover, the literature [19,20] supports the integration of AHP with other MCDM techniques to make the final results more trustworthy.…”

Section: Multi-criteria Decision-making Methodsmentioning

confidence: 99%

Assessing Supply Chain Risks in the Automotive Industry through a Modified MCDM-Based FMECA

et al. 2020

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Supply chains are complex networks that receive assiduous attention in the literature. Like any complex network, a supply chain is subject to a wide variety of risks that can result in significant economic losses and negative impacts in terms of image and prestige for companies. In circumstances of aggressive competition among companies, effective management of supply chain risks (SCRs) is crucial, and is currently a very active field of research. Failure Mode, Effects and Criticality Analysis (FMECA) has been recently extended to SCR identification and prioritization, aiming at reducing potential losses caused by lack of risk control. This article has a twofold objective. First, SCR assessment is investigated, and a comprehensive list of specific risks related to the automotive industry is compiled to extend the set of most commonly considered risks. Second, an alternative way of calculating the Risk Priority Number (RPN) is proposed within the FMECA framework by means of an integrated Multi-Criteria Decision-Making (MCDM) approach. We give a new calculation procedure by making use of the Analytic Hierarchy Process (AHP) to derive factors weights, and then the fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) to evaluate the new factor of “dependence” among the risks. The developed joint analysis constitutes a risk analysis support tool for criticality in systems engineering. The approach also deals with uncertainty and vagueness associated with input data through the use of fuzzy numbers. The results obtained from a relevant case study in the automotive industry showcase the effectiveness of this approach, which brings important value to those companies: When planning interventions of prevention/mitigation, primary importance should be given to (1) supply chain disruptions due to natural disasters; (2) manufacturing facilities, human resources, policies and breakdown processes; and (3) inefficient transport.

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Section: Multi-criteria Decision-making Methodsmentioning

confidence: 99%

Assessing Supply Chain Risks in the Automotive Industry through a Modified MCDM-Based FMECA

et al. 2020

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“…Lolli, et al [8]proposed a multi-criteria framework based on analytical hierarchy process (AHP) to classify and control inventory with intermittent demand.…”

Section: Demand Pattern Categorizationmentioning

confidence: 99%

A Hybrid Forecasting Framework with Neural Network and Time-Series Method for Intermittent Demand in Semiconductor Supply Chain

Chien

Lin

2018

IFIP Advances in Information and Communication Technology

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As the primary prerequisite of capacity planning, inventory control and order management, demand forecast is a critical issue in semiconductor supply chain. A great quantity of stock keeping units (SKUs) with intermittent demand patterns and distinctive lead-times need specific prediction respectively. It is difficult for companies in semiconductor supply chain to manage intricate inventory systems with the changeable nature of intermittent (lumpy) demand. This study aims to propose an integrated forecasting approach with recurrent neural network and parametric method for intermittent demand problems to support flexible decisions in inventory management, as a critical role in intelligent supply chain. An empirical study was conducted with product time series in a semiconductor company in Taiwan to validate the practicality of proposed model. The results suggest that the proposed hybrid model can improve forecast accuracy in demand management of semiconductor supply chain.

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“…These different notions of optimality will generally lead to different (desired) solutions. In sustainable product development (PD) problems, the objective cannot be ranked a priori since the economic, environmental, and social dimension is considered to be equally important [4,5]. The problem of PD is shown in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

Multicriteria Decision-Making in Complex Quality Evaluation of Ladies Dress Material

Misra

Salačová

Militký

2020

Autex Research Journal

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Quality is the essence of any product for consumer satisfaction. However, different people have different perception of quality. Eventually the definition of quality varies from product to product and thus it is much more complex in textile clothing material evaluation. The end use application of a specific clothing material determines what should be the parameters of quality evaluation. Thus, the evaluation based on subjective assessment becomes unpredictable and unquantifiable. Quality for dress materials is not simply a physical parameter but something called as psycho-physical parameter. In recent times, many objective evaluation systems have been developed to evaluate the apparel grade textile materials with regard to their quality parameters. However, the evaluation does not involve enough statistical treatment of data so as to obtain a parametric weighted characterization of complex quality. The current work deals with parametric approach to complex quality evaluation based on multicriteria decision-making approach for ladies dress materials. The ladies dress materials are of numerous varieties and choices across the globe. The selection and marketing of these kinds of textile materials need to be given proper emphasis as it depends not only on physical parameters but also on climate, geography, ethnic group, market trend, age group, gender, and many such complex parameters, which are not quantifiable in absolute terms. In this study, woven fabrics used for ladies dress materials are collected from the market and they were evaluated for the consumer-oriented property parameters. A parametric approach is adopted to quantify the overall quality of these dress materials. Various objective techniques were used to evaluate the comfort and esthetic parameters. A complex quality index (CQI) was estimated with weighted combination of all the contributing parameters and total quality index was calculated. Selected consumers with different education level, age, and gender were interviewed to get a statistic of their opinion about quality parameters preferred by them. This complex quality index/degree of satisfaction shows very high correlation with subjective judgment. A CQI can be evaluated for each kind of clothing material looking into their applications.

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A multicriteria framework for inventory classification and control with application to intermittent demand

Cited by 15 publications

References 44 publications

Assessing Supply Chain Risks in the Automotive Industry through a Modified MCDM-Based FMECA

Assessing Supply Chain Risks in the Automotive Industry through a Modified MCDM-Based FMECA

A Hybrid Forecasting Framework with Neural Network and Time-Series Method for Intermittent Demand in Semiconductor Supply Chain

Multicriteria Decision-Making in Complex Quality Evaluation of Ladies Dress Material

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