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The decision-making process is highly demanding. There has been an increasing tendency to incorporate human thinking, individual experience about a problem, and pure mathematical approaches. Here, a novel integrated approach is investigated and proposed to develop an advanced hybrid decision-support system based on the decision-making trial and evaluation laboratory (DEMATEL) and fuzzy cognitive maps (FCMs). Indeed, knowledge acquisition and elicitation may present distortions and difficulties finding a consensus and an interpretation. Thus, the proposed combined approach aims to examine in depth the potential to improve FCMs’ outcomes by integrating FCM with the DEMATEL approach. The combined methodology achieves at avoiding some of the drawbacks, such as the lack of a standardized FCM theoretical model. Thus, it provides advanced comparative analysis and results in better interpretation of the decision-making process. It is highlighted that the traditional FCM approach does not allow distinguishing the whole number of defined scenarios, in contrast to the hybrid one presented here, which increases the ability of users to make correct decisions. Combining the two approaches provides new capabilities to FCMs in grouping experts’ knowledge, while the DEMATEL approach contributes to refining the strength of concepts’ connections.

PurposeThe research approach is based on the concept that a failure event is rarely random and is often generated by a chain of previous events connected by a sort of domino effect. Thus, the purpose of this study is the optimal selection of the components to predictively maintain on the basis of their failure probability, under budget and time constraints.Design/methodology/approachAssets maintenance is a major challenge for any process industry. Thanks to the development of Big Data Analytics techniques and tools, data produced by such systems can be analyzed in order to predict their behavior. Considering the asset as a social system composed of several interacting components, in this work, a framework is developed to identify the relationships between component failures and to avoid them through the predictive replacement of critical ones: such relationships are identified through the Association Rule Mining (ARM), while their interaction is studied through the Social Network Analysis (SNA).FindingsA case example of a process industry is presented to explain and test the proposed model and to discuss its applicability. The proposed framework provides an approach to expand upon previous work in the areas of prediction of fault events and monitoring strategy of critical components.Originality/valueThe novel combined adoption of ARM and SNA is proposed to identify the hidden interaction among events and to define the nature of such interactions and communities of nodes in order to analyze local and global paths and define the most influential entities.

Retrofitting old plants is an excellent alternative to their replacement to prepare them for industry 4.0. Many papers are related to retrofitting, but few studies concerned the process industries. A framework to retrofit a process plant is presented and applied to a two-phase mixing plant providing a guide starting from the plant study and ending with the I4.0 paradigm implementation. The approach allowed to improve plant safety and maintainability conditions. The several issues arising during the retrofitting can be related to its multidisciplinarity aspects, the recursion in the definition of new variables to be monitored, and the information flow management.

[EN] The economy of the future is experiencing a fundamental change in its structure, determined mainly by demographic factors. To this regard, the silver economy concept has been coined, relative to the consumer segment of people aged 50 or over. The present study aims at providing a state-of-the-art literature review about this field of research, using VOSviewer software, a freely available tool to construct bibliometrics maps. The analysis of these maps is presented, providing useful insight on the main topics within the silver economy field of study., This research has been supported by the "Programme to support the academic career of the faculty of the Universitat Politecnica de Valencia 2019/2020" in the project 'Enterprise and Supply Chain Resilience Enhancement' granted to Dr. Raquel Sanchis who wish to thank Universita Politecnica delle Marche, particularly the Department of Industrial Engineering and Mathematical Science for the support, during her stay, in the development of the present research.

Industry 4.0 is evolving through technological advancements, leveraging information technology to enhance industry with digitalisation and intelligent activities. Whereas Industry 5.0 is the Age of Augmentation, striving to concentrate on human-centricity, sustainability, and resilience of the intelligent factories and synergetic industry. The crucial enhancer for the improvements accomplished by digital transformation is the notion of ‘digital triplet D3’, which is an augmentation of the digital twin with artificial intelligence, human ingenuity, and experience. digital triplet D3 encompasses intelligent activities based on human awareness and the convergence among cyberspace, physical space, and humans, in which Implementing useful reference hierarchy is a crucial part of instigating Industry 5.0 into a reality. This paper depicts a digital triplet which discloses the potency of retrofitting a conventional drilling machine. This hierarchy included the perceptive level for complex decision-making by deploying machine learning based on human ingenuity and creativity, the concatenated level for controlling the physical system’s behaviour predictions and emulation, the observing level is the iterative observation of the actual behaviour of the physical system using real-time data, and the duplicating level visualises and emulates virtual features through physical tasks. The accomplishment demonstrated the viability of the hierarchy in imitating the real-time functionality of the physical system in cyberspace, an immaculate performance of this paradigm. The digital triplet’s complexity was diminished through the interaction among facile digital twins, intelligent activities, and human awareness. The performance parameters of the digital triplet D3 paradigm for retrofitting were eventually confirmed through appraising, anomaly analysis, and real-time monitoring.

The emerging scenario designed by digital technologies connected to Industry 4.0 is pushing towards increasingly sustainable companies. Access to the multiple benefits of digitalization (such as increased productivity, flexibility, efficiency, quality, lower consumption of resources, and the improvement of worker safety) is possible by purchasing new-generation machinery. However, thanks to smart retrofitting processes, companies can extend the shelf life of machinery without replacing it entirely. This work aims to present a framework to assess the sustainability of implementing a smart retrofitting process in old machines as an alternative to replacement from a triple bottom line (economic, environmental, and social) perspective. Due to the multidimensional and multidisciplinary variables that the proposed framework must consider, a multicriteria decision-making process is developed to identify the best transition solution from Industry 3.0 to 4.0. Then, we analyze a case study in which, thanks to the previously proposed methodology, two types of smart retrofitting on a column drill are compared with three replacement options for the same machine tool. In conclusion, the case study shows that retrofitting in the context of Industry 4.0 (or smart retrofitting), despite its high acquisition cost, is the best solution in terms of sustainability, and that this is because the smart retrofitting solution not only positively influences all parameters of digitization but also has a strong impact on the safety criterion.

The Green Supply Chain has proposed to innovate industrial production by implementing a radical perspective change: reconcile economy and ecology. This study aims to contribute to the realisation of a new idea of eco-sustainable industrialisation. Anyone making decisions within any dynamic system faces serious difficulties. For this reason, the proposed study analyses this system using Fuzzy Cognitive Maps arriving at the formation of a real map of the causal relationships between the concepts identified, then divided by areas of membership. In doing so, the most relevant factors affecting the Green Supply Chain decision-making process have been identified and analysed.

Effective maintenance policies can support companies to deal with process interruptions and consequently, to prevent significant profit losses. Moreover, the proliferation of structured and unstructured data due to production plants validates the application of knowledge discovery in databases techniques to increase processes’ reliability. In this paper, an innovative maintenance policy is proposed. It aims at both predicting components breakages through association rule mining and determining the optimal set of components to repair in order to improve the overall plant’s reliability, under time and budget constraints. An experimental campaign is carried out on a real-life case study concerning an oil refinery plant. Finally, numerical results are discussed considering different blockage categories and number of components and by varying some significant input parameters.

In this study, the life cycle assessment (LCA) has been applied to analyze the greenhouse gas (GHG) emissions and energy requirements in the post-harvest life of apples from the Trentino-South Tyrol region (Northern Italy). Data were collected over four years from two commercial apple packinghouses. The key processes in the supply chain were identified based on direct observation, and different scenarios for conservation, packaging, and transport, as well as the source of electricity were analyzed. The results showed that the packaging was the main contributor to both the global warming potential (GWP, from 68 to 98 gCO2eq per kg of apples) and to the cumulative energy demand (from 1.3 to 1.9 MJ/kg). The cooling process (i.e., initial refrigeration and maintaining the cool temperature) that the fruit undergoes before being stored was the second largest contributor to the environmental effects produced during the apple post-harvest. The use of renewable energy is an attractive option to drastically reduce the GWP of this phase. If long transportation distances need to be covered (for example for export, or distances exceeding 300 km), using rail transport or shipping could cut down substantially the environmental costs. The most favorable environmental performances during the post-harvest of the apple include the storage by controlled atmosphere (CA), the delivering of fruits in large reusable plastic bins and their transport over short distances.

This paper presents an educational approach for teaching Industry 4.0 concepts to maintenance and safety operators involved in industrial processes. A Learning-by-doing approach was introduced to assess the impact of learning by doing and knowledge sharing on designing maintenance and safety solutions based on Industry 4.0 concepts to build experience and improve decision-making skills. To this end, we proposed a pilot course to train industrial operators in the field of new technologies so that they could continue their work effectively. Specifically, the development of the course began with a needs assessment of the perspective participants, followed by an outline of the objectives and course structure. The course was adapted to the different educational and technical backgrounds of the participants (i.e., experienced operators who were digital immigrants and non-experienced operators who were digital natives). The results of the course were assessed through a survey, which allowed us to evaluate the operators’ perception of the learning approach and the contribution to improving the operators’ competencies and abilities. The results highlighted that the educational approach facilitated the teaching of maintenance and safety principles, promoting operators’ attention and participation. The difference in the learning level that we observed between the younger and older operators was also highlighted by the survey results. A dichotomy was revealed between the younger operators, who showed a greater understanding of the explained technologies, and the older operators, who required longer learning times. In this way, both types of participant could benefit from mutual collaboration and teamwork to improve their respective weaknesses.

An essential step in the implementation of predictive maintenance involves the health state analysis of productive equipment in order to provide company managers with performance and degradation indicators which help to predict component condition. In this paper, a supervised approach for health indicator calculation is provided combining the Grey Wolf Optimisation method, Swarm Intelligence algorithm, and Fuzzy Cognitive Maps. The k-neighbors algorithms is used to predict the Remaining Useful Life of an item, since, in addition to its simplicity, they produce good results in a large number of domains. The approach aims to solve the problem that frequently occurs in interpolation procedures: the approximation of functions belonging to a chosen class of functions of which we have no knowledge. The proposed algorithm allows maintenance managers to distinguish different degradation profiles in depth with a consequently more precise estimate of the Remaining Useful Life of an item and, in addition, an in-depth understanding of the degradation process. Specifically, in order to show its suitability for predictive maintenance, a dataset on NASA aircraft engines has been used and results have been compared to those obtained with a neural network approach. Results highlight how all of the degradation profiles, obtained using the proposed approach, are modelled in a more detailed manner, allowing one to significantly distinguish different situations. Moreover, the physical core speed and the corrected fan speed have been identified as the main critical factors to the engine degradation.

By using a functional requirement analysis, through Design for Manufacture and Assembly and Design for Environment principles, this paper aims at showing a new design method to improve the overall assembly features and environmental sustainability of a packaging solution. This method provides to rank functional requirements according to three different design specifications and also to the number of relationships they have with each other. At the same time, a ranked order of importance for the packaging parts has been realised, considering the number of performed functions. The purpose of this method is to support the designers in focusing their attention on the most important packaging parts and, at the same time, giving them a clear idea of which are the most important functional requirements to be satisfied. This study has been focused on domestic household packaging, but the provided method can be extended to any particular packaging solution and its findings are still valid. According to the Design for Environmental perspective, the actual and the new resulting packaging solutions have been then compared through Life Cycle Assessment method. The results have shown the new packaging solution being able to cut down the environmental impacts, on average, of approximately 30%.

Supply Chain Resilience has been broadly studied during the last decades, especially within the academic community. Therefore, the present research article aims to provide a broad view of the scientific literature about Resilience within Supply Chain research. First, a trend analysis of these topics research and publications is presented. Then, a more detailed analysis is shown, in order to produce bibliometric maps and tables summarizing the main scientific trends under these topics: the latter analysis will provide useful insight of the most used keywords on the subject and the connections among them.

The aim of this study is to evaluate, from an environmental point of view, the performance of various technologies applied to the treatment of municipal landfill leachate. The study has been led in an Italian wastewater treatment plant and it applies the principles of the Life Cycle Assessment (LCA) technique, using ReCiPe as the assessment method. This study shows how the operating stage of a wastewater treatment plant, that applies chemical and physical treatments, can affect the following four environmental impact categories: “Freshwater Eutrophication”, “Freshwater Ecotoxicity”, “Marine Ecotoxicity” and “Human Toxicity”. Within this operating stage, the study shows the relevant environmental impacts generated by the use of polyaluminum chloride (PAC) as a coagulant chemical agent and sodium hydroxide (caustic soda) as a pH control chemical agent. In order to investigate these results, and to discover more eco-friendly alternatives, two LCA comparisons have been carried out, comparing respectively the above two agents to analogous and common substitutes: ferric chloride as a coagulant agent and calcium hydroxide (lime) as a pH control agent. These comparisons demonstrate the higher environmental impacts of the use of ferric chloride over PAC and of sodium hydroxide over calcium hydroxide. Ferric chloride has shown to have more than double the environmental impact of PAC in 9 environmental categories out of the 10 considered, while calcium hydroxide has been able to cut down the negative environmental impacts of the sodium hydroxide of more than 65% in all the environmental categories. Considering the highly positive environmental results achieved from our study, whenever possible, a substitution of calcium hydroxide to sodium hydroxide and of PAC to ferric chloride is strongly recommended.

This study aims at improving the environmental sustainability of an existing honey production supply chain, pursuing the Sustainable Supply Chain Management philosophy and the Life Cycle Assessment principles. Focusing the attention on the packaging stage and, in particular, on the most commonly used honey packaging solution, the glass jar, this study assesses the environmental burdens associated with its manufacturing, distribution and final disposal. Once the “AS-IS” honey packaging situation of an Italian province has been analyzed, parallel packaging reuse scenarios and redistribution supply chains are modelled, involving different levels of collaboration between the honey producers and the provincial beekeeping consortium. These scenarios have been then compared to the AS-IS situation, taking into account five environmental factors important for the honeybee's survival: the carbon dioxide equivalent emission, the triethylene glycol equivalent emissions into water and soil, the sulfur dioxide equivalent emission into air and the m2 equivalent reduction of organic arable land per year. The outcomes show how the adoption of a packaging reuse policy together with a producer collaboration policy could bring, in five years, to reduce those factors on average of 16% (with a 10% packaging reuse rate), up to more than 70% (with an 85% packaging reuse rate).

When dealing with Automated Storage and Retrieval Systems (ASRS), the allocation of items to the most convenient storage location depends on the vast amount of data produced internally (e.g., Enterprise Resource Planning, Manufacturing Enterprise Systems) and externally (e.g. Supply Chain Management). Moreover, a proper item allocation in the warehouse has a strong influence on the warehouse saturation levels and picking times. In this perspective, the present work proposes the application of data-driven algorithms for managing items in an Automated Storage and Retrieval System (ASRS) in order to reduce the picking times and storage space. Specifically, a four-layer framework is adopted for collecting data produced by different information sources and analyzing them through a data-driven approach. The analytics layer is performed by combining the Association Rule Mining (ARM) technique, to investigate the network of influences among data collected, and a simulation approach for assessing the feasibility of the proposed implementation. The Association Rule Mining allows company managers to identify the components that should be located on the same tray in the ASRS, defining the couples of items frequently picked together in order to reduce the total picking time. The proposed approach is applied to the case study of a shoe manufacturing company to explain the research approach and show how the implementation of the data-driven methodology can provide valuable support in defining item allocation and picking rules. The proposed Association Rule Mining method is new in this context and it has shown a positive impact in comparison to traditional solutions of warehouse management, providing a complete overview of the items’ interactions and identifying communities of items that define local and global patterns and locate influential entities.

The economic world is in constant evolution and companies are struggling to adapt and, in the meantime, tackle disturbances. To address these challenges has emerged the need to develop resilient Supply Chains. This study offers a modularization of the Supply Chain Resilience Triangle, an intuitive tool for assessing the performance of a Supply Chain during a disruption, through an accurate study of the various factors influencing the resilience of the Supply Chain.

This paper examines the preliminary performance analysis outcomes of the New Product Devolpment (NPD) process drawing attention to the human behavioural factors. It aims at evaluating a possible solution to improve the NPD process focusing the attention on the team combination. Timed Coloured Petri Nets (TCPNs) have been used to model the NPD process because, thanks to the possibility of using colours, it is possible to investigate profoundly different situations and compare different solutions. Two categories of colours have been defined to manage the TCPN model: “Operational” (OPg), referred to the traditional activities information, and “Behavioural” (BHg), connected to the personal skills of the operators. The results highlight that, if the human behavioural factors are considered during the process evolution, jointly to engineering approaches, it is possible to improve the system performance considerably and, referring to the Team Leaders personality, they need to manifest an extroverted and perceiving personality in conjunction with mastering project management discipline. The analysed outcomes derive from the simulated evolution of the NPD process considering several involved companies. They represent the starting point for a results validation on real NPD execution to define, according to specific professionals, an efficient and efficacy policy in the NPD team forming. A model, simulating human activity, cannot conform with a real case because the interaction among human resources is well different from, for instance, among raw materials and machinery, a relationship that could be automated and regulated by a well-precise model.

The Resource Constrained Scheduling Project (RCSP) is one of the most complex tasks in the sector of project management. Many researchers devoted effort during the last years to solve this criticality. Moreover, interesting studies analyse the problem regarding mathematical formulation. In so doing, the exact and/or heuristic solutions tools allow extending the analysis to a broad range of Operation Management problems. The proposed article describes a new approach for project/process modelling based on Timed Coloured Petri Nets (TCPNs), to simplify the resource allocation in a resource-constrained problem. In particular, its utilisation provides a robust formalism to represent and analyse parallel systems. The TCPNs utilisation allows analysing interdependencies, criticality, substitution, conflicting resource priorities and variations in the availability of resources. This paper proposes a new model and highlights the usefulness of the model for real-time activity scheduling in a resource-constrained project environment. A case study for an industrial project is described to provide a systematic analysis of the proposed tool.

In the literature, many applications of Digital Twin methodologies in the manufacturing, construction and oil and gas sectors have been proposed, but there is still no reference model specifically developed for risk control and prevention. In this context, this work develops a Digital Twin reference model in order to define conceptual guidelines to support the implementation of Digital Twin for risk prediction and prevention. The reference model proposed in this paper is made up of four main layers (Process industry physical space, Communication system, Digital Twin and User space), while the implementation steps of the reference model have been divided into five phases (Development of the risk assessment plan, Development of the communication and control system, Development of Digital Twin tools, Tools integration in a Digital Twin perspective and models and Platform validation). During the design and implementation phases of a Digital Twin, different criticalities must be taken into consideration concerning the need for deterministic transactions, a large number of pervasive devices, and standardization issues. Practical implications of the proposed reference model regard the possibility to detect, identify and develop corrective actions that can affect the safety of operators, the reduction of maintenance and operating costs, and more general improvements of the company business by intervening both in strictly technological and organizational terms.

The paper describes an approach for analyzing the use of a Laser-Guided Vehicle (LGV) in the context of the small and medium-sized enterprise. The use of LGVs is an efficient solution to provide more flexibility in the context of Just-In-Time production; however, the investment cost can limit this application. A methodology has been proposed in this work to analyze the technical feasibility of using an LGV in the manufacturing industry of customized products. The test case focuses on the study of a laser-guided system to optimize the handling of molds for customized production. In this scenario, an LGV is proposed to substitute manual carts used for moving molds from the warehouse to the injection machines. The traditional path included an intermediate station for pre-heating the molds in hot-air ovens. The proposed solution includes the study of an induction heating system on the LGV to optimize time and energy consumption.

The environmental impact of friction stir welding process vs. welding parameters was evaluated and analysed in detail. To this purpose, butt joints in AA5754 aluminum alloy sheets were obtained at different rotational and welding speeds. All input and output data, in terms of materials, energies and emissions, were collected and analyzed using a life cycle assessment software in order to evaluate the environmental impact index. Sound weld was used as functional unit and all energy and material flows were based on it. The results given by the life cycle assessment analysis has shown that the environmental impact of friction stir welding is strongly affected by rotational and welding speeds. The environmental impact was also related to the mechanical properties of joints, expressed as ultimate tensile strength and ultimate elongation.

The present study analyzed the Italian scenario of OHSAS 18001 certified companies. In particular, the aim of this work is to investigate the relationships between four factors that companies have to consider during BS OHSAS 18001 implementation: the decisional factors which influence the company's choice to adopt certification, the success and failure factors, responsible for successful or unsuccessful OHSAS-18001 implementation and the company's improvement. A thorough literature review concerning OHSAS-18001 and Health, Safety and Environment (HSE) Systems was conducted in order to identify the main factors that have an impact on OHSAS 18001 implementation. The researchers studied the relationships between these factors and a structural equation modeling (SEM) approach was employed to test the hypothesized model. Results indicate that the factors that push Italian companies to adopt certification have a positive correlation with the success factors necessary for the implementation of the OHSAS-18001 standard. This means that decisional factors are fundamental for successful implementation and for company improvement. Moreover, decisional factors also have a strong influence on enterprise improvement. In fact certification is seen as a prerequisite for survival in the current market, allowing insurance benefits, a greater control of potential risks and a reduction in staff injuries. However a remarkable increase in bureaucracy, a lack of specialized personnel and high certification costs have been identified as the main failure factors in unsuccessful BS OHSAS 18001 implementation. This research study also highlights the interest of companies in reducing their social responsibility by implementing the OHSAS 18001 standard. In conclusion this study has an important role in describing the current Italian scenario, providing interesting information for both researchers and practitioners since it defines the main enabling factors for successful BS OHSAS 18001 implementation and the main problems that practitioners could face.

The transformation from traditional industry to Industry 4.0 can bring many benefits in various spheres, from efficiency to safety. However, this transition involves adopting technologically advanced machinery with a high level of digitization and communication. The costs and time to replace obsolete machines could be unsustainable for many companies while retrofitting the old machinery. To make them ready to the Industry 4.0 context, they may represent an alternative to the replacement. Even if there are many studies related to retrofitting applied to machinery, there are very few studies related to the literature process industry sector. In this work, we propose a case study of a two-phase mixing plant that needed to be enhanced in the safety and maintainability conditions with reasonable times and costs. In this regard, the Digital Twin techniques and Deep Learning algorithms will be tested to predict and detect future faults, not only already visible and existing malfunctions. This approach strength is that, with limited investments and reasonable times, it allows the transformation of an old plant into a smart plant capable of communicating quickly with operators to increase its safety and maintainability.

In a complex and unpredictable world, nowadays classic risk management techniques are often nor sufficient neither adequate to face the occurring disruptive events. When black swans events (low probability—high impact events) take place, many supply chains are not qualified to tackle those happenings in an efficient way. A resilient approach can fill this expertise gap, providing the necessary know-how and mindset qualities to supply chain players in order to tackle those rising disruptions better. In particular, resilience is a key component in the fashion industry supply chain. In the last decades, many companies declined and retired, while several thrived. The resilience approach was one of the keys that divided successful firms from the unprofitable ones. This research provides a broad view of the literature review about resilience approach within the fashion industry supply chain. Furthermore, in ordimpact of possible disruptionser to assist academics and supply chain decision makers, this study will extensively show the state of the art of the current methodologies used to assess and measures resilience in one’s supply chain.

In industrialized countries, packaging waste is one of the major issues to deal with, representing around 35% of the total municipal solid waste yearly generated. Therefore, an analysis and an environmental assessment of packaging systems are necessary. This paper aims at analyzing and comparing the environmental performances of two different packaging for domestic hoods. It shows how, through a packaging redesign, it is possible to obtain a reduction of the environmental impacts. This study has been performed in accordance with the international standards ISO 14040/14044, by using attributional Life Cycle Assessment (LCA) from Cradle to Gate. The functional unit has been defined as the packaging of a single household hood. Primary data have been provided by a household hood manufacturer, while secondary data have been obtained from the Ecoinvent database. LCA software SimaPro 8.5 has been used to carry out the life cycle assessment, and ReCiPe method has been chosen for the life cycle impact assessment (LCIA) stage. The results have shown the new packaging model being able to cut down the environmental impacts of approximately 30%. These outcomes may be used by household manufacturers to improve performances and design solutions of their different packaging.

Today, different sectors are using Life Cycle Assessment methods to manage risk, create regulation and well-considered policy ad to protect the brand and redesign processes, products and services. Despite their prevalence, Life Cycle Assessment concepts are still not well known in many academic and industrial contexts. In the past, the inability to see the full life cycle of our actions resulted in unexpected consequences in many fields such as increased cancer rates, species and habitat destruction and high levels of waste (both financial and material). This study aims at developing a new educational approach for learning Life Cycle Assessment concepts by applying them to the daily practice of the preparation of meals. The work has been accomplished through several learning games, called “Cook & Teach”, in an engineering course at Universita Politecnica delle Marche (Ancona, Italy). This study intends to investigate three principal aspects. The first aspect is the change in the student's knowledge of sustainable development. The second is the change in the student's perception of his professional skill development following completion of the project. The last aspect is related to how the student's perception of his motivation and engagement in the project is related to the change in professional skill development. In addition, the game sessions analyzed and discussed in this work show the educational power and training value of the “Cook & Teach” to LCA topics and in particular how the new game facilitates product selection, as confirmed by all of the actors involved. The results obtained highlight that this new educational approach to teach LCA principles stimulated the students' attention and participation.

This study compares the environmental impacts related to the production of cotton yarn from cultivation to washing and drying, when cotton is supplied by four companies located in four different countries (Egypt, China, India and the USA). Interesting results have been obtained from cultivation scenarios where the productivity influences the value of the environmental impact associated to each country. The highest greenhouse effect is produced by the Indian company, with 0.89 kg of CO 2 equivalent (per 1 kg of cotton). Fuel consumption and Ammonium nitrate are the first items of greenhouse effect in all companies because of their extensive use and the lack of rotation with other unprofitable crops. In Chinese and Egyptian companies the irrigation sources are severely threatened and it is necessary to switch from a flood irrigation to a drip irrigation system. The production phase of cotton yarn provides an impact equal to 2.81 CO 2 kg-equivalent. The most critical impacts of cotton yarn production are due to Dyeing (1.24 CO 2 kg-eq.) and Spinning (0.64 CO 2 kg-eq.) phases and they are essentially connected to reactive reagents and pigments, electrical and thermal energy. Regarding thermal energy consumptions some improvements in dyeing plants (recover cooling water, return steam condensate to boilers or reuse different process waters) may allow the company to decrease in CO 2 emission by 41.7%. Moreover a reduction in CO 2 emission by 34.6% can be achieved in the spinning phase using an optimized suction tube in conjunction with adjustable inverter control.

Purpose – The purpose of this paper is to investigate the perceptions toward issues and benefits of ISO 9000 certification in seven different productive firms of a company leader in the production and commercialization of heating systems for water and environment, for industrial and domestic use.Design/methodology/approach – An innovative vertical analysis on ISO 9000 was conducted by an empirical study on a representative sample of the supply chain of a company in the heating sector. Questionnaires were used which covered several topics related to the reasons for pursuing ISO certification, to the installation phase and the identified benefits and issues.Findings – The results of the questionnaire outline that the reasons behind the implementation of ISO 9000 were mainly externally driven (customer request, company image and competitive advantages). The vertical analysis carried out demonstrated a shared vision between the main company and the seven selected productive plants involved in the study on the...

To achieve important improvements of the process performance measures such as quality, speed, service, and cost, fundamental rethinking and redesign of the underlying process is required. Numerous corporations have been forced to change their processes in order to survive in a highly competitive market. In this paper, a framework based on the IDEF3 methodology, and dynamic simulation for process analysis and reengineering is presented. This approach is used for analysis, diagnosis, and management of process changes represented with an IDEF3 model. To evaluate the impact of changes considered, support the process analysis, and to model performance of the proposed process, a dynamic simulation is used. Specifically, an Italian airport has been studied in order to demonstrate as the Business Process Reengineering could be a useful tool for helping managers in their decisions. The objective of this work is to demonstrate the performance breakthrough of a BPR technique to achieve dramatic improvements in critical measures of contemporary performance with respect to quality service and speed in the airlines cargo handling process.

This work aims at analysing the environmental strategies developed by fashion companies in order to identify the most important stakeholders involved in the strategy, the environmental practices carried out and the competitiveness impacts. A conceptual model, based on Association Rules (AR), has been proposed for investigating the network of influences among the environmental strategy, the environmental management practices and the environmental competitiveness and profitability of the companies. The research has been conducted through a survey submitted to fashion companies operating in Textile, Clothing and Leather (TCL) sectors. Results indicate that “customers” and “suppliers” are the most important stakeholders to be involved in the environmental strategy. A greater compliance and a risk reduction can be reached when the Financial institutions, Environmental NGOs, Rivals and Shareholders are involved in the environmental strategy. In this regards, results highlighted the importance of Environmental auditing programme for suppliers and Sustainable disclosures. Moreover, in fashion sector, the companies that pursued “Lower cost” as competitive advantage aim at obtaining from environmental strategy a great access to capital and lower cost of capital.

This paper conducts a comparative assessment of the environmental impacts of three methods of treating primary clarifier effluent in wastewater treatment plants (WWTPs) through life cycle assessment methodology. The three technologies, activated sludge (AS), high rate anaerobic-aerobic digestion (HRAAD), and trickling filter (TF), were assessed for treatment of wastewater possessing average values of biochemical oxygen demand and total suspended solids of 90 mg L−1 and 70 mg L−1, respectively. The operational requirements to process the municipal wastewater to effluent that meets USEPA regulations have been calculated. The data for the AS system were collected from the East Honolulu WWTP (Hawaii, USA) while data for the HRAAD system were collected from a demonstration-scale system at the same plant. The data for the TF system were estimated from published literature. Two different assessment methods have been used in this study: IMPACT 2002+ and TRACI 2. The results show that TF had the smallest environmental impacts and that AS had the largest, while HRAAD was in between the two but with much reduced impacts compared with AS. Additionally, the study shows that lower sludge production is the greatest advantage of HRAAD for reducing environmental impacts compared with AS.

Issues related to health and safety at work, such as accidents at work, are one of the most important areas of action for global social policy. This paper presents a fuzzy cognitive map (FCM) approach to explore the importance of the relevant factors in industrial plants. For this purpose, industrial plants are described in terms of factors that affect injury risk and the causal relationships involved. In this work, the injuries in an Italian refinery have been studied. The company in this account has a system for monitoring and controlling the machinery but has a large number of minor injuries at work. The causes of these injuries have been found in human behaviours. To analyse the injuries, it is necessary to investigate what individual-level concerns are involved in the perception of risk. For this investigation, an FCM permits us to build a schema of the perception of risk. The resulting analysis of all of these schemas has allowed us to define a method that generically permits a determination of the causes for each type of injury. In fact, it has been possible to determine that factors such as poor attention and concentration or fatigue are the main causes of injuries at work. In light of the results obtained, managers can define appropriate control procedures to diminish the occurrences of the injuries.

PurposeThe purpose of this paper is to present the application of a procedure for the quality control of stainless steel tubes produced for automotive exhaust systems from a leading company in the steel sector, based on the Delphi method in accordance with the ISO/TS 16949:2009 and the ISO 9000:2008. Using Delphi methodology, it was possible to identify the main problems in the production lines object of the study, the main defects and their causes. Statistical methods were used to monitor process compliance and capacity. The panel of experts involved in Delphi method was able to identify causes of non‐compliance and suggest corrective actions.Design/methodology/approachThe quality procedure implemented involves the application of the Delphi method and the ISO/TS 16949:2009 standard in conjunction with ISO 9000:2008 to the production line of welded tubes for exhaust systems. The statistical methods used to monitor the process were mainly control charts. Capability index, Cp and Cpk, were used to measure the process attitude to produce compliant outputs. Dimensional data were acquired by non‐destructive testing on diameters and X‐R charts were used to graphically represent the process state of control. Destructive tests were performed to monitor the welding quality and P‐chart were used to assess the proportion of nonconforming units.FindingsIn this work, a procedure was developed in order to characterize the production process of TXM tubes realized in the line 31 of the leader company plant. The use of Delphi methodology, in order to incorporate experts opinions in the quality control of stainless steel tubes, was one of the main points of this work. The panel of experts worked together to identify process issues, define their causes and propose corrective actions. The paper provides an overview about the quality approach of one of the world's largest companies in the production of steel and shows also how the statistical tools are used in order to manage process behavior.Originality/valueThe value of this paper is to illustrate an innovative approach to a real life quality problem; it demonstrates how the application of qualitative and quantitative quality instruments in accordance with technical specification can help in increasing and maintaining product compliance and in optimizing the management of resources.

This research work focuses on the application of life-cycle assessment methodology to determine the carbon footprint of different players involved in a supply chain of the textile sector. A case study of a product by a textile leader company was carried out. This study demonstrates that, in the textile chain, the main contribution to the greenhouse effect is provided by the electrical and thermal energy used and by the transportation (since different production phases are delocalised in a wide range that goes from South Africa, Italy, Romania and all around the world, from the distribution centre to the stores). The Monte Carlo analysis has been used in order to obtain, for each calculated impact, not only the average value but also the distribution curve of the results characterised by uncertainty parameters. Moreover, a sensitivity analysis was carried out to evaluate the impact of management choices such as: • a change in the transportation modality, from aeroplane to boat; • a combination of road and ...

The management of occupational injury is of strategic importance in a company from the organizational, engineering and economic point of view. This work is an attempt to apply data mining techniques to data regarding accidents in a medium-sized refinery. Several techniques were adopted in order to identify the important relationships between risk level and immediate/root causes and corrective actions. As a Data Mining technique were tested: Negative Binomial Regression (NBR), Chi-Squared Automatic Interaction Detection (CHAID); Exhaustive CHAID; Classification And Regression Trees (CART); Quick, Unbiased, Efficient Statistical Tree (QUEST), Artificial Neural Network (ANN) and Neuro-Fuzzy Systems (FIS). The comparison carried out in this study shows through a real application the flexibility and advantages of using the neuro-fuzzy network, a typical soft computing tool. Using these innovative techniques to analyse injury data this study aims to: • obtain a classification of input data according to their importance and/or influence on the risk level in injuries; • assess how a variation in one or more pieces of input data can effect occupational injury and subsequently carry out a sensitivity analysis concerning the probability, the consequences and risks of the injurie events; The analyses carried out indicated important relationships between the variables, providing useful decision-making rules which can be followed when adopting measures for improvement.

In this work a case study is proposed in order to define the main steps carried out to design a cross-docking in Fano, a city located in the centre of Italy, in Pesaro-Urbino province. The cross-docking project analysed in this work is made up of four steps: - first of all an analysis of the main parameters that characterize a cross-docking was carried out; - region characterization: economical and environmental analysis; - road traffic analysis of goods for the geographical area considered; - demand analysis of a sample of firms (factory firms and freight operators) using questionnaire; analysis of results. Results obtained from this work show that the cross-docking allows economic improvements and pollution reduction.