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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.

One of the most important challenges of high-risk industries regards environmental risk management. In all sectors characterized by high-risk processes, failure can lead to catastrophic environmental events, so it is necessary to have a model capable of extracting useful information from the data collected and able to provide company managers with decision-making tools. In this work, a framework has been developed to manage environmental risk in a process industry. In order to analyse adverse environmental events, data provided by different sources and geographically dispersed repositories have been considered. A conceptual model, based on Association Rules (AR), has been developed to investigate the network of influences among data collected. Moreover, a Social Network Analysis has been used to represent the association rules, providing a complete overview of the factors’ interaction and to identify communities of nodes in order to define local and global patterns and locate influential entities. To test the proposed approach and assess its impact on environmental management strategies, a medium-sized refinery case study has been analysed. The big data analytics approach proposed in this work, taking into consideration a wide set of objective and predictive variables, allowed the refinery managers to show new cause–effect correlations in refinery processes regarding adverse environmental event typology, immediate and root causes, refinery plant area involved in the adverse event, risk index and corrective actions.

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.

This work aims at developing a method for analysing the domino effect among concepts affecting Supply Chain Resilience. The proposed method allows connecting concepts at many different levels (e.g....

Despite companies’ efforts to develop lean thinking in their industrial context, the implementation of many lean projects has not been consistently successful, often resulting in delay, failure, ab...

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.

In the literature, when lean is associated with resilience the focus is mainly on developing leaner and more resilient supply chains underrating the importance of organisations as communicating ent...

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).

In this work, a new procedure called Human Factor Risk Management (HFRM) was developed in order to integrate Human Factor in a Refinery Risk Management System. Taking into consideration historical data regarding Environmental Accidents, Near miss, Injuries and Operating accidents occurred in a refinery over the last years a panel of experts defined the performance shaping factors (PSFs) and risk associated with adverse events. A conceptual model, based on Association Rules (AR), has been proposed for investigating the network of influences among adverse event typology, human error causes, refinery plant area involved in the adverse event, performance shaping factors (PSFs), risk index and corrective actions. The results obtained using the association rules method proved to be useful for assessing human practices and human factors which influence high-risk situations. The human factor analysis carried out in this paper was planned as a dynamic process and can be repeated systematically. The association rules technique, taking into consideration a wide set of objective and predictive variables, shows new cause–effect correlations in refinery processes never described previously, highlighting possible adverse events and supporting decision-making in these areas.

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.

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.

This work aims at developing a new procedure, based on RFID technology, in order to reduce clinical risk and to streamline surgical instruments sterilization processes. An automatic identification and data storage will allow the hospital to minimize problems connected with bacterial infection, loss of surgical instruments and waste of time due to instruments counting and tracking. This procedure was developed at an Italian hospital of medium size, with particular attention to the processes that are carried out in Sterile Surgical Unit (SSU), in operating theatre and in the business units. The sterilization process of surgical instruments has been analysed as it was always implemented up until the year 2013, identifying any related problems. The process has been then reengineered in order to assess the changes involved and pinpointing further opportunities for improvement. Processes were modelled using the AIO WIN software, which supports the IDEF0 method. The activities, related to different management options, have been analysed and compared in terms of costs and savings.

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.

Worldwide modern organisation is continuously crossed by a great number of information but frequently information is not accurate, the needed information is not generated or it cannot be easily identified and, more, the information cannot flow through the whole organisation. This paper proposes the application of lean thinking in the field of information management. In the areas of manufacturing and production, the lean thinking is well known but usually the importance of a holistic approach is neglected and the improvement involves only the production and logistic areas and there is not a specific focus on the lean information management. We applied lean thinking to information management in order to improve the performance of an automotive company. We analysed the as-is company condition, we identified the present muda and we introduced the necessary changes. Then, we verified the modification efficiency through the calculation of a performance index. The paper proposes an interesting and exhaustive cas...

Purpose – The purpose of this paper is to uncover the significance of quick changeovers in the packaging line of a pharmaceutical company. Using an integration of different lean practices, the study aims to reduce the batch change and changeover time up to 50 per cent, increasing overall equipment effectiveness by 25 per cent. Design/methodology/approach – The paper gives setup instructions and guidelines for preparing the standardized setup procedure without ignoring the actual constraints in a pharmaceutical company. It uses a case study to generate an integrated setup reduction approach, utilizing single-minute exchange of die tools (SMED) in combination with suppliers, inputs, process, outputs and customers (SIPOC), Kanban, 5S techniques and Total Productive Maintenance (TPM) indexes to achieve faster setups. Findings – The SMED approach helps the pharmaceutical company to eliminate unwanted activities and to externalize and reduce the internal activities by simplification or standardization. The application of other tools, such as 5S and Kanban tool-kits, allowed the company to optimize the process and reduce the standard deviation of the changeover times. Good manufacturing practice (GMP) procedures of the pharmaceutical sector limit the conversion of internal setup elements to external setup elements. Originality/value – The paper demonstrates the practical application of SMED, showing how it can bring real breakthroughs in productivity to a pharmaceutical company. Moreover, in this work, we highlight the importance of an integration of different lean practices to reduce variation in the changeover time. In particular, the standardization of setup tasks and the increased reliability in the material supply chain, in addition to reducing the changeover mean time can also reduce the standard deviation of the setup process time.

The implementation of a RFID system is discussed in this study, for the division of the offices and furniture of an Italian company that is a leader in the furniture industry. This system allowed for a type of "electronic identity card" to ensure the authenticity of products and their traceability. Through Business Process Re-Engineering (BPR) methods, the "AS IS" and "TO BE" scenarios obtained as a result of the proposed changes are analysed. In particular, two production phases are analysed in this work: the sewing and inventory. The differences between the "AS IS" and "TO BE" systems are analysed to highlight the improvement obtained using the RFID system. An analysis of the management and implementation costs of new scenarios is developed.

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...

The successful implementation of any innovation requires an understanding of its benefits and costs. This study examines the changes in costs and benefits associated with technology process innovation adoption as the innovation diffuses across healthcare field. Using RFID as an exemplar technology, the study shows the importance of benefits and costs associated with technological process innovation. The analysed case study provides the order of magnitude of the problems that can be solved with the introduction of the new system and it shows the information provided as output by the informatics system associated. For technology managers in general, the study has identified the profile of costs and benefits associated with technology adoption, and offered some indication of how this profile changes depending on the stage of technology evolution. This study proposed the implementation of a drug management system based on RFID technology. The study also revealed as the adoption of RFID technology allows perfect traceability of the drug throughout the system. In addition, this technology greatly reduces the action of operators in the operations of the management and administration and therefore the occurrence of errors.

The aim of this work was to optimize and test a new type of experimental blancher designed to carry out a wide range of processes, with the possibility to also use a combination of water and steam. This new type of blancher was developed in order to overcome many drawbacks of conventional blanching and drying methods, including low energy efficiency, long processing times, quality deterioration and environmental problems, through the use of a new system to control the blancher temperature. In particular this work focuses on the problem of optimizing the steeping process for blanching rice , using design of experiment techniques and analyzing the response to cooking of two varieties of rice. The first variety was simply polished while the second was parboiled, i.e. the latter variety of rice had previously been subjected to hydrothermal processing to gelatinize the starch. The study was also extended to find the optimal steeping conditions for blanching both the varieties. A fundamental requirement was to identify and analyze the optimal conditions for the independent variables, time and temperature, which come into play during the blanching process. To that end the statistical method of MultiSimplex optimization proved to be a valid tool.

This paper aims at developing a new methodology for designing and managing a supply chain (SC) and, at the same time, for evaluating the performance of every stakeholder involved in a production chain. The methodology proposed has been applied to a footwear supply chain and is based on coloured Petri nets (CPNs). The supply chain analysed in this paper is a complex production system consisting of a network of manufacturers and service suppliers related to logistics systems that provide transportation and storage. The model developed uses coloured, timed Petri nets to represent a supply chain and it is such that resources are the Petri Net (PN) places, the tokens are jobs, orders and/or products, while the colours represent job attributes. These colours are used to encode different data types and values that are attached to tokens. A “coloured token” represents a specific production order or a certain amount of a particular material supplied. Thus, it can be processed in different ways and it can be easily...

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.

This paper presents the development of an innovative fuzzy-QFD based methodology for characterizing customer rating of food products. The method has been tested on different samples of extra virgin olive oil to verify its suitability. The results demonstrated the effectiveness of such multi-criterion technique not only for the design and development of new products that meet customers’ requirements, but also for testing the quality of existing ones. The main innovation of the method, consists in the application of the fuzzy logic to address the issue, common in many decisional techniques, of dealing with data deriving from subjective verbally expressed evaluations that cannot be treated with mathematical models. The objective of this work was to test the combined assessment technique based on quality function deployment and fuzzy logic method for determining which characteristics of extra virgin olive oil influence most of the acceptance of the consumers toward the product. The relationship between consumer expectations, defined by a market survey, and main attributes of the examined products were assessed by means of the House of Quality (HOQ). The results obtained allowed to classify the quality of different brands of olive oil with respect to customer preferences.

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 ...

PurposeThe purpose of this paper is to carry out the business process re‐engineering (BPR) of a surgical ward in a hospital in order to improve the efficiency of the ward.Design/methodology/approachThis work was developed using a case study on a surgical ward. In this type of ward, in which scheduled and unscheduled operations often have to coexist and be managed, ways to minimise patient inconvenience need to be studied. A framework based on event‐driven process chains (EPCs) methodology, the entity‐relationship model and discrete event simulation is presented to define and analyse the current state of a surgical ward and design a future system. The modelling of the processes, activities and sub‐activities, which took up a great amount of ward resources, allowed a what‐if analysis to be developed which simulates various scenarios and assesses their performance.FindingsUsing Delphi methodology, it was possible to identify a number of areas for improvement: number of operating sessions, preparation of the operating rooms for each operation, availability of specific surgical instruments. Moreover, the discrete event simulation approach led to an understanding of the most efficient management choices.Originality/valueThe decision to use Delphi methodology for the information collection stage before starting the BPR process is not found in other studies in the literature. Moreover, the use of models based on EPCs methodology allowed the panel of experts to develop models to examine and understand the resource requirements of medical assessment units and to provide a framework or develop standards that hospital developers and clinical managers can consult.

The aim of this research work is to perform a feasibility analysis to evaluate the introduction of an identification system based on Radio Frequency Identification technology (RFId) in the management of the spare parts warehouse in a process industry that produces petrochemicals products. In order to map the situation of the different activities related to the warehouse management, the Business Process Reengineering (BPR) methodology has been used to have a clear and complete representation of the actual situation "AS IS", and his critical aspects and the future situation after the reengineer phase "TO BE". The activities related to the different management options have been analyzed ad compared in terms of cost and saving. Cost for implementing the RFId system has been evaluated.

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.

The aim of this study was to develop business process reengineering for a supply chain of fourth range vegetable products and to set up a computerised system for managing product traceability. A framework based on event-driven process chains (EPCs) methodology, the entity-relationship model (ERM) and activity-based costing (ABC) is used to define and analyse the current state of a supply chain and design a future system. The production chain of fourth range vegetable has seldom been developed on an industrial scale. We chose to reengineering a supply chain according to an industrial type production starting from the production of seed within the company itself and covering all the stages of cultivation, processing and marketing of the product. The models of traceability processes, the project of a software using ARIS and the integration of this software in the management system of a supply chain allowed the company studied in this work to develop a framework for the integration of the information flow and for cost analysis.

In this case study, the Theory of Constraints and Risk Assessment are applied to the turnaround process of an IGCC (Integrated Gasification Combined Cycle) plant. Turnaround project has been analysed as it had always been implemented up to 2006, identifying any related problems and inconsistencies, and then to describe the reengineering of this process, assessing and emphasizing the changes involved and identifying further opportunities for improvement. The aim of the study is to develop a prioritization method for Work Packages, within the Critical Chain context, in order to minimize the risks related to accidents in the refinery plants. This study addresses the applicability and necessity of the risk analysis process to examine and evaluate the schedule and cost features of a turnaround project. A comparison between the performance obtained for the turnaround using classic project management techniques and results obtained using the new planning system showed that the proposed method allowed the company to maximize the quality and safety of work and to minimize the turnaround time and cost. We also found that while improvement is feasible for turnaround in certain areas, the development of a maintenance improvement strategy that appreciates the needs of different stakeholders (providers, manufacturing units, etc.) is indispensable. Turnaround improvement strategy relates to policy, anticipation of problems, responsiveness of people and monitoring outcomes.

The management of failure analysis has a strategic importance within a refinery from the organizational, engineering and economic point of view. The determination of an algorithm, that allows a methodical and as far as possible automatic approach to management of failure data, can make substantial improvements in the organization of work and in the decision-making processes. A panel of expert, made up of academicians and refinery operators, was formed in order to develop a Risk-Based Inspection and Maintenance (RBI&M) procedure. RBI&M procedure developed comprises six modules: identification of the scope, functional analysis, risk assessment, risk evaluation, operation selection and planning, J-factor computation and operation realization. Taking into consideration historical data regarding Near Accidents, Operating Drawbacks, Occupational and Environmental Accidents occurred in refinery over the last years the panel of expert defined a risk matrix in order to evaluate the risk associated to critical events and maintenance activities. Five probability classes and five severity categories, that take into account four impact categories (Health and Safety, Environmental, Economic and Reputation), have been defined. This paper reports the application of the RBI&M method to two specific stages in the maintenance activities of the refinery, i.e. the oil refinery turnaround and work orders management. The panel of expert developed heuristic methods in order to apply RBI&M procedure to the two cases allowing the refinery to minimize the overall risk taking into consideration the limits in term of time and budget (in turnaround case) and of human resources (in the management of work orders). The results have highlighted a clear improvement in the indices which measure the quality of maintenance.

This study was aimed both at assessing the risk of occupational injury, considering the probability and consequences of injuries that may occur, and at identifying any general factors which may affect the incidence of injuries. The analysis in this paper refers to occupational injuries which occurred in a 5-year period (2002-2006) in an Italian region. Any activities to prevent occupational risks and injuries need to involve an adequate information technology system. Classification and prediction are necessarily involved in this type of data analysis in order to obtain models which describe important categories of data, or to predict the trend of future data. Neuro-fuzzy networks are considered a powerful tool, especially when dealing with these problems of data mining. The aim of this paper was to show through a real application the flexibility and advantages of using the neuro-fuzzy network, a typical soft computing tool, for an occupational injury study. Using these innovative techniques to analyse injury data coming from an Italian region, this study aims to: - obtain a classification of input data according to their importance and/or influence on the trend 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 frequency of the injuries and their consequences; - verify the possibility of comparing past data with the predicted trend in injuries, using the neuro-fuzzy networks trained with the past data. Language: en