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Elia Balugani
Department of Sciences and Methods for Engineering, University of Modena and Reggio Emilia, Via Amendola 2, Padiglione Morselli, 42122 Reggio Emilia, Italy

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Journal article
Published: 13 April 2021 in Expert Systems with Applications
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Life Cycle Assessment quantifies the multi-dimensional impact of goods and services and can be handled by Multi-Criteria Decision Analysis. In Multi-Criteria Decision Analysis, Robust Ordinal Regression manages all the compatible preference functions at once when assessing a set of alternatives and a group of preferences on reference alternatives. Robust Ordinal Regression is thus a versatile method of reducing the cognitive effort required by decision makers for eliciting their preference structures in Life Cycle Assessment, although it does not directly operate on noisy alternatives and requires Stochastic Multicriteria Acceptability Analysis to deal with such scenarios. We propose integrating a dimensionality reduction technique, Principal Component Analysis, and Robust Ordinal Regression methods, to reduce the problem dimensionality and ensure the actual problem features are considered. A generated dataset, a dataset from literature and a Life Cycle Assessment case study are used to test the effectiveness of the proposed methods.

ACS Style

Elia Balugani; Francesco Lolli; Martina Pini; Anna Maria Ferrari; Paolo Neri; Rita Gamberini; Bianca Rimini. Dimensionality reduced robust ordinal regression applied to life cycle assessment. Expert Systems with Applications 2021, 178, 115021 .

AMA Style

Elia Balugani, Francesco Lolli, Martina Pini, Anna Maria Ferrari, Paolo Neri, Rita Gamberini, Bianca Rimini. Dimensionality reduced robust ordinal regression applied to life cycle assessment. Expert Systems with Applications. 2021; 178 ():115021.

Chicago/Turabian Style

Elia Balugani; Francesco Lolli; Martina Pini; Anna Maria Ferrari; Paolo Neri; Rita Gamberini; Bianca Rimini. 2021. "Dimensionality reduced robust ordinal regression applied to life cycle assessment." Expert Systems with Applications 178, no. : 115021.

Journal article
Published: 02 December 2020 in International Journal of Production Economics
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Due to the main peculiarities of spare parts, i.e. intermittent demands, long procurement lead times and high downtime costs when the parts are not available on time, it is often difficult to find the optimal inventory level. Recently, Additive Manufacturing (AM) has emerged as a promising technique to improve spare parts inventory management thanks to a ‘print on demand’ approach. So far, however, the impact of AM on spare parts inventory management has been little considered, and it is not yet clear when the use of AM for spare parts inventory management would provide benefits over Conventional Manufacturing (CM) techniques. With this paper we thus aim to contribute to the field of AM spare parts inventory management by developing decision trees that can be of support to managers and practitioners. To this aim, we considered a Poisson-based inventory management system and we carried out a parametrical analysis considering different part sizes and complexity, backorder costs and part consumption. Moreover, we evaluated scenarios where the order-up-to level is limited to resemble applications with a limited storage capacity. For the first time, the analysis was not limited to just one AM and one CM technique, but several AM and CM techniques were considered, also combined with different post-process treatments, for a total of nine different sourcing alternatives. In addition, the economic and technical performance of the different sourcing options were obtained thanks to an interdisciplinary approach, where experts from production economics and material science were brought together.

ACS Style

Fabio Sgarbossa; Mirco Peron; Francesco Lolli; Elia Balugani. Conventional or additive manufacturing for spare parts management: An extensive comparison for Poisson demand. International Journal of Production Economics 2020, 233, 107993 .

AMA Style

Fabio Sgarbossa, Mirco Peron, Francesco Lolli, Elia Balugani. Conventional or additive manufacturing for spare parts management: An extensive comparison for Poisson demand. International Journal of Production Economics. 2020; 233 ():107993.

Chicago/Turabian Style

Fabio Sgarbossa; Mirco Peron; Francesco Lolli; Elia Balugani. 2020. "Conventional or additive manufacturing for spare parts management: An extensive comparison for Poisson demand." International Journal of Production Economics 233, no. : 107993.

Journal article
Published: 26 February 2020 in Sustainability
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The concepts of resilience and sustainability appear multi-dimensional and correlated, depending on the context. Operational sustainability practices can enhance the resilience of a firm, and support its growth. This study aims at analyzing the impact of a sustainability strategy, measured by means of a sustainability maturity index (SMI), on the financial performance of a company. Since the SMI is strictly correlated to resilience capabilities, the performed analysis represents a first level integration of the sustainability and resilience indicators in a common framework. A data sample from 53 organizations was collected through structured interviews and analyzed to identify possible relationships between the SMI and the financial performance indexes. The analysis does not support commonly reported arguments: we show that profitability does not show a significant relationship with sustainable strategic intent. Interestingly, firm country of origin, size of the organization, and market focus, likewise, do not have a significant relationship with SMI. Arguably, multi-dimensional company performance, including both financial and non-financial measures, should be considered to assess the impact of sustainability practices. Moreover, further investigations are needed to capture firms’ nonfinancial indicators of performance that are related to sustainability and resilience, for building up a unified framework enabling trade-off analysis.

ACS Style

Elia Balugani; Maria Angela Butturi; Delroy Chevers; David Parker; Bianca Rimini. Empirical Evaluation of the Impact of Resilience and Sustainability on Firms’ Performance. Sustainability 2020, 12, 1742 .

AMA Style

Elia Balugani, Maria Angela Butturi, Delroy Chevers, David Parker, Bianca Rimini. Empirical Evaluation of the Impact of Resilience and Sustainability on Firms’ Performance. Sustainability. 2020; 12 (5):1742.

Chicago/Turabian Style

Elia Balugani; Maria Angela Butturi; Delroy Chevers; David Parker; Bianca Rimini. 2020. "Empirical Evaluation of the Impact of Resilience and Sustainability on Firms’ Performance." Sustainability 12, no. 5: 1742.

Conference paper
Published: 22 January 2020 in Advances in Intelligent Systems and Computing
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For a PROMETHEE II method used to rank concurrent alternatives both preference functions and weights are required, and if the weights are unknown, they can be elicited by leveraging present or past partial rankings. If the known partial ranking is incorrect, the eliciting methods are ineffective. In this paper a logistic regression method for weight elicitation is proposed to tackle this scenario. An experiment is carried out to compare the logistic regression method performance against a state-of-the-art linear weight elicitation method, proving the validity of the proposed methodology.

ACS Style

Elia Balugani; Francesco Lolli; Maria Angela Butturi; Alessio Ishizaka; Miguel Afonso Sellitto. Logistic Regression for Criteria Weight Elicitation in PROMETHEE-Based Ranking Methods. Advances in Intelligent Systems and Computing 2020, 474 -479.

AMA Style

Elia Balugani, Francesco Lolli, Maria Angela Butturi, Alessio Ishizaka, Miguel Afonso Sellitto. Logistic Regression for Criteria Weight Elicitation in PROMETHEE-Based Ranking Methods. Advances in Intelligent Systems and Computing. 2020; ():474-479.

Chicago/Turabian Style

Elia Balugani; Francesco Lolli; Maria Angela Butturi; Alessio Ishizaka; Miguel Afonso Sellitto. 2020. "Logistic Regression for Criteria Weight Elicitation in PROMETHEE-Based Ranking Methods." Advances in Intelligent Systems and Computing , no. : 474-479.

Journal article
Published: 25 December 2019 in IFAC-PapersOnLine
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Complexity measurement based on the Shannon information entropy is widely used to evaluate variety and uncertainty in supply chains. However, how to use a complexity measurement to support control actions is still an open issue. This article presents a method to calculate the relative complexity, i.e., the relationship between the current and the maximum possible complexity in a Supply Chain. The method relies on unexpected information requirements to mitigate uncertainty. The article studies two real-world Supply Chains of the footwear industry, one competing by cost and quality, the other by flexibility, dependability, and innovation. The second is twice as complex as the first, showing that competitive priorities influence the complexity of the system and that lower complexity does not ensure competitivity.

ACS Style

Miguel A. Sellitto; Francesco Lolli; Bianca Rimini; Elia Balugani. Complexity Measurement in Two Supply Chains with Different Competitive Priorities. IFAC-PapersOnLine 2019, 52, 1699 -1704.

AMA Style

Miguel A. Sellitto, Francesco Lolli, Bianca Rimini, Elia Balugani. Complexity Measurement in Two Supply Chains with Different Competitive Priorities. IFAC-PapersOnLine. 2019; 52 (13):1699-1704.

Chicago/Turabian Style

Miguel A. Sellitto; Francesco Lolli; Bianca Rimini; Elia Balugani. 2019. "Complexity Measurement in Two Supply Chains with Different Competitive Priorities." IFAC-PapersOnLine 52, no. 13: 1699-1704.

Review article
Published: 10 September 2019 in Applied Energy
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Replacing fossil fuels with renewable energy sources is considered as an effective means to reduce carbon emissions at the industrial level and it is often supported by local authorities. However, individual firms still encounter technical and financial barriers that hinder the installation of renewables. The eco-industrial park approach aims to create synergies among firms thereby enabling them to share and efficiently use natural and economic resources. It also provides a suitable model to encourage the use of renewable energy sources in the industry sector. Synergies among eco-industrial parks and the adjacent urban areas can lead to the development of optimized energy production plants, so that the excess energy is available to cover some of the energy demands of nearby towns. This study thus provides an overview of the scientific literature on energy synergies within eco-industrial parks, which facilitate the uptake of renewable energy sources at the industrial level, potentially creating urban-industrial energy symbiosis. The literature analysis was conducted by arranging the energy-related content into thematic categories, aimed at exploring energy symbiosis options within eco-industrial parks. It focuses on the urban-industrial energy symbiosis solutions, in terms of design and optimization models, technologies used and organizational strategies. The study highlights four main pathways to implement energy synergies, and demonstrates viable solutions to improve renewable energy sources uptake at the industrial level. A number of research gaps are also identified, revealing that the energy symbiosis networks between industrial and urban areas integrating renewable energy systems, are under-investigated.

ACS Style

M.A. Butturi; F. Lolli; Miguel Sellitto; Elia Balugani; R. Gamberini; B. Rimini. Renewable energy in eco-industrial parks and urban-industrial symbiosis: A literature review and a conceptual synthesis. Applied Energy 2019, 255, 113825 .

AMA Style

M.A. Butturi, F. Lolli, Miguel Sellitto, Elia Balugani, R. Gamberini, B. Rimini. Renewable energy in eco-industrial parks and urban-industrial symbiosis: A literature review and a conceptual synthesis. Applied Energy. 2019; 255 ():113825.

Chicago/Turabian Style

M.A. Butturi; F. Lolli; Miguel Sellitto; Elia Balugani; R. Gamberini; B. Rimini. 2019. "Renewable energy in eco-industrial parks and urban-industrial symbiosis: A literature review and a conceptual synthesis." Applied Energy 255, no. : 113825.

Erratum
Published: 20 June 2019 in Journal of Cleaner Production
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ACS Style

Martina Pini; Francesco Lolli; Elia Balugani; Rita Gamberini; Paolo Neri; Bianca Rimini; Anna Maria Ferrari. Corrigendum to “Preparation for reuse activity of waste electrical and electronic equipment: Environmental performance, cost externality and job creation” [J. Clean. Prod. 222 (2019) 77–89]. Journal of Cleaner Production 2019, 232, 1529 -1530.

AMA Style

Martina Pini, Francesco Lolli, Elia Balugani, Rita Gamberini, Paolo Neri, Bianca Rimini, Anna Maria Ferrari. Corrigendum to “Preparation for reuse activity of waste electrical and electronic equipment: Environmental performance, cost externality and job creation” [J. Clean. Prod. 222 (2019) 77–89]. Journal of Cleaner Production. 2019; 232 ():1529-1530.

Chicago/Turabian Style

Martina Pini; Francesco Lolli; Elia Balugani; Rita Gamberini; Paolo Neri; Bianca Rimini; Anna Maria Ferrari. 2019. "Corrigendum to “Preparation for reuse activity of waste electrical and electronic equipment: Environmental performance, cost externality and job creation” [J. Clean. Prod. 222 (2019) 77–89]." Journal of Cleaner Production 232, no. : 1529-1530.

Journal article
Published: 06 March 2019 in Journal of Cleaner Production
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The European Waste Electrical and Electronic Equipment system introduced measures to encourage both the reduction of the amount of electronic waste and its separation to prepare for reuse. The aim of this study is compare the environmental performance, external costs and social aspect of the whole life cycle of new and reconditioned electrical and electronic equipment by adopting Life Cycle Assessment methodology. Five electrical and electronic equipment categories were investigated and the data collection was made on an Italian context. The refurbishing of breakdown electrical and electronic equipment was assessed by considering different sets of faulty components (Scenario A and B) and a total of 25 scenarios were studied. Moreover, both attributional and consequential life cycle inventory modelling framework were adopted to represent the investigated scenarios. The outcomes highlighted that the preparation for reuse process leads to obtaining a sustainable electronic device than the new one, depending on which set of components are replaced. Adopting Scenario B with the attributional model, the environmental damage of reconditioned electrical and electronic equipment decreases compared to the new one. Conversely, the consequential approach determines an environmental credit for all repaired electronic devices except for one category; in particular, Scenario A produced the largest environmental advantage. The analyses of external costs and social aspects confirm that the preparation for reuse activity allows to obtain a more sustainable product than a new one. For these two latter aspects, the results showed a turnaround passing from attributional model to consequential one. Noting the variability in results adopting both different life cycle inventory modelling framework and set of replaced components, the Life Cycle Assessment practitioner, that conducted the study, should help the decision-makers to determine which scenario is more sustainable accomplishing an adequate choice.

ACS Style

Martina Pini; Francesco Lolli; Elia Balugani; Rita Gamberini; Paolo Neri; Bianca Rimini; Anna Maria Ferrari. Preparation for reuse activity of waste electrical and electronic equipment: Environmental performance, cost externality and job creation. Journal of Cleaner Production 2019, 222, 77 -89.

AMA Style

Martina Pini, Francesco Lolli, Elia Balugani, Rita Gamberini, Paolo Neri, Bianca Rimini, Anna Maria Ferrari. Preparation for reuse activity of waste electrical and electronic equipment: Environmental performance, cost externality and job creation. Journal of Cleaner Production. 2019; 222 ():77-89.

Chicago/Turabian Style

Martina Pini; Francesco Lolli; Elia Balugani; Rita Gamberini; Paolo Neri; Bianca Rimini; Anna Maria Ferrari. 2019. "Preparation for reuse activity of waste electrical and electronic equipment: Environmental performance, cost externality and job creation." Journal of Cleaner Production 222, no. : 77-89.

Journal article
Published: 01 March 2019 in The Breast
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ACS Style

F. Giovanardi; F. Lolli; Elia Balugani; D. Pezzuolo; G. Prati; C. Degli Esposti; D. Cerioli. VALETUDO project: VAlidation study of the LEarning machine Technique (neUral networks) for big Data in the breast tumor in ReggiO Emilia region, Italy. The Breast 2019, 44, S87 .

AMA Style

F. Giovanardi, F. Lolli, Elia Balugani, D. Pezzuolo, G. Prati, C. Degli Esposti, D. Cerioli. VALETUDO project: VAlidation study of the LEarning machine Technique (neUral networks) for big Data in the breast tumor in ReggiO Emilia region, Italy. The Breast. 2019; 44 ():S87.

Chicago/Turabian Style

F. Giovanardi; F. Lolli; Elia Balugani; D. Pezzuolo; G. Prati; C. Degli Esposti; D. Cerioli. 2019. "VALETUDO project: VAlidation study of the LEarning machine Technique (neUral networks) for big Data in the breast tumor in ReggiO Emilia region, Italy." The Breast 44, no. : S87.

Journal article
Published: 14 February 2019 in Computers & Industrial Engineering
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The training of suppliers and inbound quality inspectors is a common strategy to increase the quality performance of the supply chain but, under budget constraints, these actors compete for a limited amount of training hours. The proposed model aims to allocate the available training hours so as to minimise a total quality cost function composed of prevention, appraisal, and failure costs; it also sets the inspection rates defining the inspection policies assigned to suppliers. The relationship between decision variables and costs is expressed through organisational and individual learning-forgetting curves, for suppliers and quality inspectors respectively, and the effect of the training hours on quality improvement is measured in terms of failure rates. To the best of our knowledge, a total quality cost model with such decision variables is new in the related literature, as it is a model including both organisational and individual learning-forgetting phenomena. A nonlinear optimisation approach was adopted to solve this complex problem. The experimental section includes a decision trees analysis of simplified scenarios in order to interpret the model functioning, as well as a complex numerical example to extrapolate managerial insights.

ACS Style

Francesco Lolli; Elia Balugani; Rita Gamberini; Bianca Rimini. Quality cost-based allocation of training hours using learning-forgetting curves. Computers & Industrial Engineering 2019, 131, 552 -564.

AMA Style

Francesco Lolli, Elia Balugani, Rita Gamberini, Bianca Rimini. Quality cost-based allocation of training hours using learning-forgetting curves. Computers & Industrial Engineering. 2019; 131 ():552-564.

Chicago/Turabian Style

Francesco Lolli; Elia Balugani; Rita Gamberini; Bianca Rimini. 2019. "Quality cost-based allocation of training hours using learning-forgetting curves." Computers & Industrial Engineering 131, no. : 552-564.

Journal article
Published: 31 January 2019 in International Journal of Production Research
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ACS Style

Elia Balugani; Francesco Lolli; Rita Gamberini; Bianca Rimini; M. Z. Babai. A periodic inventory system of intermittent demand items with fixed lifetimes. International Journal of Production Research 2019, 57, 6993 -7005.

AMA Style

Elia Balugani, Francesco Lolli, Rita Gamberini, Bianca Rimini, M. Z. Babai. A periodic inventory system of intermittent demand items with fixed lifetimes. International Journal of Production Research. 2019; 57 (22):6993-7005.

Chicago/Turabian Style

Elia Balugani; Francesco Lolli; Rita Gamberini; Bianca Rimini; M. Z. Babai. 2019. "A periodic inventory system of intermittent demand items with fixed lifetimes." International Journal of Production Research 57, no. 22: 6993-7005.

Journal article
Published: 24 November 2018 in Expert Systems with Applications
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Today, almost everybody has a smartphone and applications have been developed to help users to take decisions (e.g. which hotel to choose, which museum to visit, etc). In order to improve the recommendations of the mobile application, it is crucial to elicit the preference structures of the user. As problems are often based on several criteria, multicriteria decision aiding methods are most adequate in these cases, and past works have proposed indirect eliciting approaches for multicriteria decision aiding methods. However, they often do not aim of reducing as much as possible the cognitive efforts required by the user. This is prerequisite of mobile applications as they are used by everybody. In this work, the weights to assign to the evaluation criteria in a PROMETHEE-based ranking approach are unknown, and therefore must be elicited indirectly either from a partial ranking provided by the user or from the selection of his/her most preferred alternative into a subset of reference alternatives. In the latter case, the cognitive effort required by the decision-maker is minimal. Starting from a linear optimisation model aimed at searching for the most discriminating vector of weights, three quadratic variants are proposed subsequently to overcome the issues arising from the linear model. An iterative quadratic optimisation model is proposed to fit the real setting in which the application should operate, where the eliciting procedure must be launched iteratively and converge over time to the vector of weights, which are the weights that the user implicitly assigns to the evaluation criteria. Finally, three experiments are performed to confirm the effectiveness and the differences between the proposed models.

ACS Style

Francesco Lolli; Elia Balugani; Alessio Ishizaka; Rita Gamberini; Maria Angela Butturi; Samuele Marinello; Bianca Rimini. On the elicitation of criteria weights in PROMETHEE-based ranking methods for a mobile application. Expert Systems with Applications 2018, 120, 217 -227.

AMA Style

Francesco Lolli, Elia Balugani, Alessio Ishizaka, Rita Gamberini, Maria Angela Butturi, Samuele Marinello, Bianca Rimini. On the elicitation of criteria weights in PROMETHEE-based ranking methods for a mobile application. Expert Systems with Applications. 2018; 120 ():217-227.

Chicago/Turabian Style

Francesco Lolli; Elia Balugani; Alessio Ishizaka; Rita Gamberini; Maria Angela Butturi; Samuele Marinello; Bianca Rimini. 2018. "On the elicitation of criteria weights in PROMETHEE-based ranking methods for a mobile application." Expert Systems with Applications 120, no. : 217-227.

Journal article
Published: 31 October 2018 in Production Planning & Control
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ACS Style

F. Lolli; Elia Balugani; Alessio Ishizaka; R. Gamberini; B. Rimini; A. Regattieri. Machine learning for multi-criteria inventory classification applied to intermittent demand. Production Planning & Control 2018, 30, 76 -89.

AMA Style

F. Lolli, Elia Balugani, Alessio Ishizaka, R. Gamberini, B. Rimini, A. Regattieri. Machine learning for multi-criteria inventory classification applied to intermittent demand. Production Planning & Control. 2018; 30 (1):76-89.

Chicago/Turabian Style

F. Lolli; Elia Balugani; Alessio Ishizaka; R. Gamberini; B. Rimini; A. Regattieri. 2018. "Machine learning for multi-criteria inventory classification applied to intermittent demand." Production Planning & Control 30, no. 1: 76-89.

Journal article
Published: 06 September 2018 in IFAC-PapersOnLine
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The Assembly Line Balancing Problem (ALBP) represents one of the most explored research topics in manufacturing. However, only a few contributions have investigated the effect of the combined abilities of humans and machines in order to reach a balancing solution. It is well-recognized that human beings learn to perform assembly tasks over time, with the effect of reducing the time needed for unitary tasks. This implies a need to re-balance assembly lines periodically, in accordance with the increased level of human experience. However, given an assembly task that is partially performed by automatic equipment, it could be argued that some subtasks are not subject to learning effects. Breaking up assembly tasks into human and automatic subtasks represents the first step towards more sophisticated approaches for ALBP. In this paper, a learning curve is introduced that captures this disaggregation, which is then applied to a stochastic ALBP. Finally, a numerical example is proposed to show how this learning curve affects balancing solutions.

ACS Style

F. Lolli; E. Balugani; R. Gamberini; B. Rimini; V. Rossi. A human-machine learning curve for stochastic assembly line balancing problems. IFAC-PapersOnLine 2018, 51, 1186 -1191.

AMA Style

F. Lolli, E. Balugani, R. Gamberini, B. Rimini, V. Rossi. A human-machine learning curve for stochastic assembly line balancing problems. IFAC-PapersOnLine. 2018; 51 (11):1186-1191.

Chicago/Turabian Style

F. Lolli; E. Balugani; R. Gamberini; B. Rimini; V. Rossi. 2018. "A human-machine learning curve for stochastic assembly line balancing problems." IFAC-PapersOnLine 51, no. 11: 1186-1191.

Journal article
Published: 06 September 2018 in IFAC-PapersOnLine
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A case study on continuous process control based on fuzzy logic and supported by expert knowledge is proposed. The aim is to control the coal-grinding operations in a cement manufacturing plant. Fuzzy logic is based on linguistic variables that emulate human judgment and can solve complex modeling problems subject to uncertainty or incomplete information. Fuzzy controllers can handle control problems when an accurate model of the process is unavailable, ill-defined, or subject to excessive parameter variations. The system implementation resulted in productivity gains and energy consumption reductions of 3% and 5% respectively, in line with the literature related to similar applications.

ACS Style

Miguel A. Sellitto; Elia Balugani; Rita Gamberini; Bianca Rimini. A Fuzzy Logic Control application to the Cement Industry. IFAC-PapersOnLine 2018, 51, 1542 -1547.

AMA Style

Miguel A. Sellitto, Elia Balugani, Rita Gamberini, Bianca Rimini. A Fuzzy Logic Control application to the Cement Industry. IFAC-PapersOnLine. 2018; 51 (11):1542-1547.

Chicago/Turabian Style

Miguel A. Sellitto; Elia Balugani; Rita Gamberini; Bianca Rimini. 2018. "A Fuzzy Logic Control application to the Cement Industry." IFAC-PapersOnLine 51, no. 11: 1542-1547.

Journal article
Published: 06 September 2018 in IFAC-PapersOnLine
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Inventory control is one of the main activities in industrial plant management. Both process owners and line workers interact daily with stocks of components and finite products, and an effective management of these inventory levels is a key factor in an efficient manufacturing process. In this paper the algorithms k-means and Ward’s method are used to cluster items into homogenous groups to be managed with uniform inventory control policies. This unsupervised step reduces the need for computationally expensive inventory system control simulations. The performance of this methodology was found to be significant but was strongly impacted by the intermediate feature transformation processes.

ACS Style

E. Balugani; F. Lolli; R. Gamberini; B. Rimini; A. Regattieri. Clustering for inventory control systems. IFAC-PapersOnLine 2018, 51, 1174 -1179.

AMA Style

E. Balugani, F. Lolli, R. Gamberini, B. Rimini, A. Regattieri. Clustering for inventory control systems. IFAC-PapersOnLine. 2018; 51 (11):1174-1179.

Chicago/Turabian Style

E. Balugani; F. Lolli; R. Gamberini; B. Rimini; A. Regattieri. 2018. "Clustering for inventory control systems." IFAC-PapersOnLine 51, no. 11: 1174-1179.

Journal article
Published: 06 September 2018 in IFAC-PapersOnLine
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Poisson point processes are widely used to model the consumption of spare parts. However, when the items have very low consumption rates, the historical sample sizes are too small. This paper presents a modelling technique for spare parts policies in the case of items with a low consumption rate. We propose the use of chaotic models derived from the well-known chaotic processes logistic map and Hénon attractor to assess the behaviour of a set of five medium voltage motors supplying four drives in the rolling mill of a steelmaking plant. Supported by the chaotic models, we conclude that the company needs an additional motor to ensure full protection against shortages.

ACS Style

Miguel A. Sellitto; Elia Balugani; Francesco Lolli. Spare Parts Replacement Policy Based on Chaotic Models. IFAC-PapersOnLine 2018, 51, 945 -950.

AMA Style

Miguel A. Sellitto, Elia Balugani, Francesco Lolli. Spare Parts Replacement Policy Based on Chaotic Models. IFAC-PapersOnLine. 2018; 51 (11):945-950.

Chicago/Turabian Style

Miguel A. Sellitto; Elia Balugani; Francesco Lolli. 2018. "Spare Parts Replacement Policy Based on Chaotic Models." IFAC-PapersOnLine 51, no. 11: 945-950.

Journal article
Published: 01 May 2018 in International Journal of Production Economics
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Multi-criteria inventory classification groups similar items in order to facilitate their management. Data envelopment analysis (DEA) and its many variants have been used extensively for this purpose. However, DEA provides only a ranking and classes are often constructed arbitrarily with percentages. This paper introduces DEASort, a variant of DEA aimed at sorting problems. In order to avoid unrealistic classification, the expertise of decision-makers is incorporated, providing typical examples of items for each class and giving the weights of the criteria with the Analytic Hierarchy Process (AHP). This information bounds the possible weights and is added as a constraint in the model. DEASort is illustrated using a real case study of a company managing warehouses that stock spare parts.

ACS Style

Alessio Ishizaka; Francesco Lolli; Elia Balugani; Rita Cavallieri; Rita Gamberini. DEASort: Assigning items with data envelopment analysis in ABC classes. International Journal of Production Economics 2018, 199, 7 -15.

AMA Style

Alessio Ishizaka, Francesco Lolli, Elia Balugani, Rita Cavallieri, Rita Gamberini. DEASort: Assigning items with data envelopment analysis in ABC classes. International Journal of Production Economics. 2018; 199 ():7-15.

Chicago/Turabian Style

Alessio Ishizaka; Francesco Lolli; Elia Balugani; Rita Cavallieri; Rita Gamberini. 2018. "DEASort: Assigning items with data envelopment analysis in ABC classes." International Journal of Production Economics 199, no. : 7-15.

Journal article
Published: 20 March 2018 in DEStech Transactions on Engineering and Technology Research
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Perishable items, with a limited lifespan and a known expiration date, are found in a variety of industrial settings. From the food to the pharmaceutical industries, the supply chains specialize their inventory control systems to handle the added complexity. These efforts are enhanced when the items present also an intermittent consumption, characterized by frequent periods without demand mixed to highly variable positive demand events. In this paper, a novel periodic inventory control system aims at bridging the gap between these two product features, managing intermittent items with expiration dates. The proposed system performs a combinatorial analysis evaluating all the demand scenarios before and after an expiration date to measure the expected fill rate. An optimization algorithm then sets the order quantity, using mathematical properties of the system to define efficient search boundaries.

ACS Style

E. Balugani; F. Lolli; R. Gamberini; B. Rimini. INVENTORY CONTROL SYSTEM FOR INTERMITTENT ITEMS WITH PERISHABILITY. DEStech Transactions on Engineering and Technology Research 2018, 1 .

AMA Style

E. Balugani, F. Lolli, R. Gamberini, B. Rimini. INVENTORY CONTROL SYSTEM FOR INTERMITTENT ITEMS WITH PERISHABILITY. DEStech Transactions on Engineering and Technology Research. 2018; (icpr):1.

Chicago/Turabian Style

E. Balugani; F. Lolli; R. Gamberini; B. Rimini. 2018. "INVENTORY CONTROL SYSTEM FOR INTERMITTENT ITEMS WITH PERISHABILITY." DEStech Transactions on Engineering and Technology Research , no. icpr: 1.

Journal article
Published: 20 March 2018 in DEStech Transactions on Engineering and Technology Research
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One of the major shortcomings of traditional failure modes, effects and criticality analysis is the absence of any interconnection between failure ranking and a procedure for selecting the most critical maintenance/improvement tasks to be carried out. This limits the potential of FMECA for implementation in real environments. In order to bridge this gap, three different 0-1 knapsack models have been formulated. The first aims to select the failures in order to maximise cost savings. The second enriches the selection problem by also taking into account the probabilities of solving the failures with a set of maintenance tasks. The third aims to select the maintenance tasks to maximise the expected profit. In particular, the last two models make use of an evidential reasoning framework to deal with the epistemic uncertainty related to these probabilities. A dataset from a manufacturer of lift winches has been used to validate this proposal, as well as to comment on the need for group decision support systems that are capable of converting the FMECA ranking into maintenance tasks in real environments.

ACS Style

F. Lolli; R. Gamberini; E. Balugani; B. Rimini; F. Mai. FMECA-BASED OPTIMIZATION APPROACHES UNDER AN EVIDENTIAL REASONING FRAMEWORK. DEStech Transactions on Engineering and Technology Research 2018, 1 .

AMA Style

F. Lolli, R. Gamberini, E. Balugani, B. Rimini, F. Mai. FMECA-BASED OPTIMIZATION APPROACHES UNDER AN EVIDENTIAL REASONING FRAMEWORK. DEStech Transactions on Engineering and Technology Research. 2018; (icpr):1.

Chicago/Turabian Style

F. Lolli; R. Gamberini; E. Balugani; B. Rimini; F. Mai. 2018. "FMECA-BASED OPTIMIZATION APPROACHES UNDER AN EVIDENTIAL REASONING FRAMEWORK." DEStech Transactions on Engineering and Technology Research , no. icpr: 1.