Marcello Braglia, Mosè Gallo, Leonardo Marrazzini and Liberatina Carmela Santillo
This paper proposes a new metric, named Operational Space Efficiency (OpSE), intended to diagnose and quantify the inefficient use of floor space for stocking materials in…
Abstract
Purpose
This paper proposes a new metric, named Operational Space Efficiency (OpSE), intended to diagnose and quantify the inefficient use of floor space for stocking materials in industrial workstations. OpSE presents a formulation analogous to the well-known Overall Equipment Effectiveness and can be obtained as the product of three distinct indicators: Standard Compliance Effectiveness, Standards Selection Effectiveness and Design Space-usage Effectiveness.
Design/methodology/approach
This indicator scrutinizes how usefully floor space in workstations is used to temporarily stock materials in the form of raw materials, semi-finished products, parts and components. It is suited for analyzing fixed-position layouts as well as product layouts typical of repetitive manufacturing settings, such as assembly lines in the automotive sector. The proposed indicator leverages an appropriate loss structure that features those factors affecting floor space utilization in workstations with regard to supplying and stocking materials.
Findings
An Italian manufacturer in the field of electro-technology was used as an industrial case study for the application of the methodology. The application shows how the three indicators work in practice, the effectiveness of OpSE and the methodology as a whole, in diagnosing floor space usage inefficiencies and in properly addressing improvement actions of the internal logistics in industrial settings.
Originality/value
The paper scrutinizes some important Key Performance Indicators (KPIs) dealing with space usage efficiency and identifies some significant drawbacks. Then it suggests a new, inclusive structure of losses and a KPI that not only measures efficiency but also allows to identify viable countermeasures.
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Eleonora Bottani, Piera Centobelli, Mosé Gallo, Mohamad Amin Kaviani, Vipul Jain and Teresa Murino
The purpose of this paper is to propose an artificial intelligence-based framework to support decision making in wholesale distribution, with the aim to limit wholesaler…
Abstract
Purpose
The purpose of this paper is to propose an artificial intelligence-based framework to support decision making in wholesale distribution, with the aim to limit wholesaler out-of-stocks (OOSs) by jointly formulating price policies and forecasting retailer’s demand.
Design/methodology/approach
The framework is based on the cascade implementation of two artificial neural networks (ANNs) connected in series. The first ANN is used to derive the selling price of the products offered by the wholesaler. This represents one of the inputs of the second ANN that is used to anticipate the retailer’s demand. Both the ANNs make use of several other input parameters and are trained and tested on a real wholesale supply chain.
Findings
The application of the ANN framework to a real wholesale supply chain shows that the proposed methodology has the potential to decrease economic loss due to OOS occurrence by more than 56 percent.
Originality/value
The combined use of ANNs is a novelty in supply chain operation management. Moreover, this approach provides wholesalers with an effective tool to issue purchase orders according to more dependable demand forecasts.
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Marcello Braglia, Davide Castellano and Mosè Gallo
The purpose of this paper is to present a new operational approach to equipment maintenance designed to exploit the complementary nature of total productive maintenance (TPM) and…
Abstract
Purpose
The purpose of this paper is to present a new operational approach to equipment maintenance designed to exploit the complementary nature of total productive maintenance (TPM) and reliability-centered maintenance (RCM).
Design/methodology/approach
This paper focuses on the operational aspect of the maintenance practice, proposing an equipment maintenance methodology that can be suitably adopted to define a new maintenance plan or check and improve an existing one. It integrates principles and methods of TPM and RCM and uses different tools to support decision-makers and operators. It proposes several worksheets which facilitate planning and implementing maintenance activities, that range from autonomous maintenance tasks to maintainability improvement actions.
Findings
This paper exploits the complementary nature of TPM and RCM to design or improve maintenance plans for a generic system. The tools and worksheets presented can be helpful to practitioners and operators.
Originality/value
While the integration of TPM and RCM is evidently a central issue in the maintenance management context, it has received limited attention in literature. To the best of the authors’ knowledge, it lacks a structured practical equipment maintenance methodology that exploits the complementary nature of TPM and RCM. Therefore, the approach presented in this paper would fill the current gap.
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Marcello Braglia, Davide Castellano, Marco Frosolini, Mosè Gallo and Leonardo Marrazzini
The paper proposes a new workforce effectiveness metric that is a sophisticated evolution of a pre-existing overall labour effectiveness (OLE) indicator. The KPI, named revised…
Abstract
Purpose
The paper proposes a new workforce effectiveness metric that is a sophisticated evolution of a pre-existing overall labour effectiveness (OLE) indicator. The KPI, named revised OLE (ROLE), provides a structured methodology to measure in a holistic way the losses relating to labour, maintaining some formal similitude to the overall equipment effectiveness (OEE)
Design/methodology/approach
A new structure of losses is proposed to overcome the drawbacks and the difficulties that usually affect the data collection stage, referring to directly measurable quantities or, when this is not the case, suggesting a viable method to quantify the loss. Besides, this approach facilitates the comprehension of labour-related issues, suggesting potential countermeasures. The novel ROLE indicator has been defined, based on this new structure, to evaluate the labour effectiveness in batch process industries. A real case study is provided, which explains the methodology and illustrates the capability of the corresponding KPI.
Findings
The present work analyses the labour performance indexes available in literature, with the aim of evidencing those aspects that can be properly observed and quantified and, at the same time, categorizing them to identify their possible drawbacks. A new structure of losses is derived, with respect to four different categories, which may help to measure the losses themselves more effectively
Originality/value
The paper investigates some important KPIs dealing with labour performance and individuates some significant drawbacks. Then it suggests a new, inclusive structure of losses and a modified KPI that not only measures effectiveness but also allows to identify viable countermeasures.
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Giovanni Romagnoli, Mosè Gallo, Annalisa Liccardo and Ralph Riedel
Roberto De Luca, Antonino Ferraro, Antonio Galli, Mosè Gallo, Vincenzo Moscato and Giancarlo Sperlì
The recent innovations of Industry 4.0 have made it possible to easily collect data related to a production environment. In this context, information about industrial equipment �…
Abstract
Purpose
The recent innovations of Industry 4.0 have made it possible to easily collect data related to a production environment. In this context, information about industrial equipment – gathered by proper sensors – can be profitably used for supporting predictive maintenance (PdM) through the application of data-driven analytics based on artificial intelligence (AI) techniques. Although deep learning (DL) approaches have proven to be a quite effective solutions to the problem, one of the open research challenges remains – the design of PdM methods that are computationally efficient, and most importantly, applicable in real-world internet of things (IoT) scenarios, where they are required to be executable directly on the limited devices’ hardware.
Design/methodology/approach
In this paper, the authors propose a DL approach for PdM task, which is based on a particular and very efficient architecture. The major novelty behind the proposed framework is to leverage a multi-head attention (MHA) mechanism to obtain both high results in terms of remaining useful life (RUL) estimation and low memory model storage requirements, providing the basis for a possible implementation directly on the equipment hardware.
Findings
The achieved experimental results on the NASA dataset show how the authors’ approach outperforms in terms of effectiveness and efficiency the majority of the most diffused state-of-the-art techniques.
Research limitations/implications
A comparison of the spatial and temporal complexity with a typical long-short term memory (LSTM) model and the state-of-the-art approaches was also done on the NASA dataset. Despite the authors’ approach achieving similar effectiveness results with respect to other approaches, it has a significantly smaller number of parameters, a smaller storage volume and lower training time.
Practical implications
The proposed approach aims to find a compromise between effectiveness and efficiency, which is crucial in the industrial domain in which it is important to maximize the link between performance attained and resources allocated. The overall accuracy performances are also on par with the finest methods described in the literature.
Originality/value
The proposed approach allows satisfying the requirements of modern embedded AI applications (reliability, low power consumption, etc.), finding a compromise between efficiency and effectiveness.
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Tutti i Paesi che svolgono una politica del turismo tendente ad aumentare l'afflusso dei viaggiatori stranieri sul proprio territorio fanno perno e leva su quelle attrattive…
Abstract
Tutti i Paesi che svolgono una politica del turismo tendente ad aumentare l'afflusso dei viaggiatori stranieri sul proprio territorio fanno perno e leva su quelle attrattive naturali, ambientali, culturali, nelle quali sanno di eccellere. E mentre da una parte intensificano gli sforzi diretti ad accrescere e valorizzare questi elementi di maggiore interesse per i turisti provenienti dall'estero, dall'altra sviluppano una complessa attività propagandistica rivolta a divulgare nel mondo la conoscenza di tali fattori di preminenza turistica.
This article addresses three concerns about the operationalization and possible effects of exclusive talent management; the core assumptions that underpin and shape talent…
Abstract
Purpose
This article addresses three concerns about the operationalization and possible effects of exclusive talent management; the core assumptions that underpin and shape talent practices, the problem of fair talent identification and potentially adverse employee reactions.
Design/methodology/approach
This is a conceptual paper that integrates empirical research on talent and talent management with ideas from business ethics.
Findings
Organizations should not simply assume that they meet the underlying assumptions of talent management. Where the assumptions can reasonably be shown to be valid, then a framework based on a set of principles is suggested to guide organizational approaches towards responsible talent management.
Practical implications
The article provides talent practitioners with a set of principles, or at least some substantive suggestions, to be considered in the design of socially responsible talent management programmes and in programme evaluation.
Social implications
The article provides guidance for organizations wishing to improve the care of their workforce in relation to strategies of employee differentiation based on performance and potential.
Originality/value
Despite the burgeoning literature on talent management, the topic has not received much attention from an ethical and socially responsible viewpoint. This article adds to that literature and suggests further research particularly concerning the existence of real talent differences on which the entire talent management project is based.