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The recent SARS-CoV-2 outbreak has challenged companies, from both service and industry sectors, to reorganize how their business are operated in order to guarantee continuity to their operations while maintaining proper and safe conditions for workers and customers as well. In fact, a recognized preventive measure against the coronavirus spread, that has been adopted by many governments all over world, is to limit as much as possible and to make safer social interactions in the workplace. The effect of such measures is very impactful on those activities that require physical presence or a direct interaction with physical resources such as shop floors. For example, on an assembly line, it could be more difficult for operators to maintain appropriate distances if the new workplace and the new working conditions have been attentively conceived and deployed. This paper has the objective of showing how computer simulation can support companies in this complex task and, at the same time, of providing an operational tool and a case study application. Particularly, it uses a computer simulation tool (i.e., AnyLogic), to model and evaluate alternative design solutions with the aim of making the considered shop floor more resilient from the coronavirus spread perspective. We focused on the automotive sector and considered the case of a two-sided single model assembly line and the related surrounding areas. Various reconfigurations of the assembly line were considered with the aim of reducing contagion likelihood during production. In order to increase the distance between operators, we compared different solutions involving centralized and decentralized warehouses as well as collaborative robots (i.e., cobots). Each configuration was also tested with respect to the individual protection parameter, i.e., we explicitly considered the type of protection the operators use while performing their activities (no mask, surgical or FFP2 mask).

Successful flow-shop scheduling outlines a more rapid and efficient process of order fulfilment in warehouse activities. Indeed the way and the speed of order processing and, in particular, the operations concerning materials handling between the upper stocking area and a lower forward picking one must be optimized. The two activities, drops and pickings, have considerable impact on important performance parameters for Supply Chain wholesaler companies. In this paper, a new flow shop scheduling algorithm is formulated in order to process a greater number of orders by replacing the FIFO logic for the drops activities of a wholesaler company on a daily basis. The System Dynamics modelling and simulation have been used to simulate the actual scenario and the output solutions. Finally, a t-Student test validates the modelled algorithm, granting that it can be used for all wholesalers based on drop and picking activities.

This paper presents a simulation study to evaluate the current performance of a waste of electrical and electronic equipment (WEEE) management system in the north of Italy. The model takes into account several actors of the real WEEE supply network and allows to analyze different alternative scenarios for the functioning of the same network. The behavior of a real treatment plant has been simulated considering the incoming flow of waste material and all the outflows of recycled goods. The analysis is focused on two specific WEEE categories treated in the plant, which have been chosen as the most dangerous categories for the human health and the environment. Some key performance indicators (KPIs) have been defined and used to assess the performance of the current WEEE network and compare it with some alternative configurations. As it grounds on a real scenario, the model is expected to provide interesting proposals for future actions about the WEEE management in Italy.

An operator’s mistakes are frequently attributed to inexperience, which leads to a superficial management of these kinds of ‘accidental’ errors. The weakness of this traditional approach is that it isolates the wrong actions from the general systematic context, overlooking potential learning from error analysis. Modern approaches push organisations to prevent the occurrence of errors and, if necessary, to start recovery operations. The methodology proposed in this paper is aimed precisely at this second type of approach. There is a growing need for systems that show errors or deviations from the desired state of the system, leading operators towards the proper execution of tasks and reducing ‘conformance risk’. This paper presents a methodology and a simulation model of ‘Conformance Risk Aware Design’ in order to support decision-makers in modelling business processes.

This paper presents a Decision Support System (DSS) for Production Planning and Control (PPC) of a Job Shop System, operating in a Make To Order environment. Various Order Review and Release (ORR) techniques have been considered in order to tackle the problems typical of this context: high level of Work in Process, significant and not controllable throughput times and difficulties in meeting due dates. A System Dynamics (SD) approach allows to analyze the impact of the control mechanisms implemented on several system performance indicators (e.g. shop oriented and job oriented measures).

Since 1979, european and american clients had benchmarked the performance of theirs factories with those of Japanese competitors. The differences included substantially higher productivity, better quality, significantly less inventory, less space, more flexibility and much faster throughput times. Everyone knows that time is money and mangers understand the importance of quick response to customers. Lean Manufacturing techniques can be powerful in several situations, but for companies making a large variety of products with variable demand or companies making highly engineered products, Lean Manufacturing has several drawbacks. Quick Response Manufacturing (QRM) can be more effective competitive strategy for companies targeting such markets, which focuses on lead time reduction. The importance of define the lead time required in an engineer-to-order company is critical in particular during the New Product Development (NPD) process. This paper presents how to apply Quick Response Manufacturing to a manufacturing industry through the previous calculation of product components Run Time using a Fuzzy Logic approach, in order to predict whether a decision will improve lead times.

Università di Aalborg, Inghilterra, 2002

The aim of this paper is to define a methodology for determining the optimal size of the supermarket (between two workstations) through the optimization of the number of kanban in a kanban board. It also identifies some production parameters that greatly influence the optimal size of a kanban board. The approach chosen is the building of a simulation model of a single stage multi-product system with Arena, while OptQuest has been used for the next optimization phase.

The actual socio-economic dynamics and the aggressive competition on a global scale lead companies to frequent revision of their organizational structure, strategic objectives and decision-making processes. Organizations need, therefore, some methods that can provide for an innovative approach to their investigations to business problems. Even if the publishing storm around JIT may have subsided to a certain degree in recent years and many analytical methods have been published for its analysis, most of the academic papers concerning pull production suggest Discrete Event Simulation (DES) for systems management. Only little attention has been paid to System Dynamics (SD) applications. In this paper a SD model for a Single-Stage Multi-Product Kanban system will be proposed and tested under different demand patterns.

The new Industry 4.0 production paradigm has been determining a big leap ahead regarding human-machine interaction in production systems. To this extent, the introduction of collaborative/cooperative robots (COBOTs) and AR devices in industrial workplaces points out new issues concerning stress assessment in new work contexts also considering the real-time measure of stress levels to drive action on manufacturing activities. This pilot study was developed in view of finding a way to detect in real time the impending stress situation in assembly stations. We analysed stress through the administration of questionnaires and by means of an EEG tool. The sample consisted of 10 university students between 20 and 30 years old, half performed a testing session in stressful environment, while the other half not. The participants were requested to perform two different tasks, one implying only cognitive abilities and one involving also assembly activities in a controlled environment. Results show that both tasks induce comparable stress levels, indicating that it is possible to relate stress levels deriving from cognitive and assembly tasks. Moreover, these results were also used to carry out a first assessment regarding the possibility to adopt real-time EEG systems for stress monitoring.

The relationship between pharmaceutical companies and hospitals is one of the most important key factors in healthcare system. Hospitals are complex organizational structures that can be improved in order to reduce wastes from both the economic point of view and the resources employed. This leads to a progressive modification of their commercial and technological relationships with pharmaceutical companies. This paper analyses the introduction of e-collaboration models for the supply relationship between hospitals and pharmaceutical companies and presents a new and more streamlined materials purchase procedure based on e-commerce. In order to verify the real benefits and analyze the peculiarities of this approach a simulation model using the System Dynamics has been implemented.

The following paper is focused on the operating conditions for the implementation of tertiary sector marketing planning. This issue, related to the instruments and techniques from which it stems, constitutes the essential tool to compete in western markets of services. The suggested approach is oriented to design a technical model determined by conditions set selected. We used four groups of performance indicators, able to define the business strategic position of company. Afterwards using the system dynamics criteria we suggest a CLD graph which represents the interactions among the several factors that influence the company behavior related to its strategy evolution. The model is characterized for the financial market, so that the performance indicator are assessed for a bank. In the case of study we analyze a specific Bank operating in southern of Italy and we define the new marketing strategy starting from its current state and market objects through the proposed model.

In recent years there has been a significant growth in WEEE production, which actually is the most worldwide rapidly growing category of waste. The synergic action of different actors involved in environmental protection, is pushing more and more EEE manufacturers to adapt their strategies, plans and business goals in an environmentally conscious way. As time goes by, the role of the Reverse Logistics is becoming more and more critical in this field: from the mere waste management to the actual managing, planning and control of the returns flow concerning raw materials, packaging, stocks, finished products from retailers to suitable collecting, reuse, recycling or remanufacturing centers. In this paper a logical model will be described reproducing the WEEE distribution flows, considering several functional aspects. The model is then implemented by means of specific simulation software to identify critical operational aspects. Considering actual data and opportunely tuning the model some important issues will be assessed.

In production, stops due to maintenance create imbalances within the system. Let's assume that you have a series of n machines and that the i stops. In this case the i+1 would be able to continue to work only as long as stocks were available on the machine, while the i-1 could continue to work only if there was the possibility that its production would be at least temporarily placed on the machine. Therefore it is normal in order to contain the system imbalances, due to maintenance stops, introduce some buffers. In this paper we propose a simulation model to define the optimal dimension of the buffer, with regards to the maintenance policy that is applied to the production system. The model can simulate a system of units that can have very different characteristics, such as productivity or reliability, and also we can simulate an inter-operational buffer between them. The model is based on the concept of thresholds which, when crossed by the parameter of wear, determine different maintenance interventions. The cost optimization consists in determining, by simulation, at what value the thresholds should be fixed to minimize the overall maintenance cost. We use the model to determine the buffer dimension trend depending on the cost of the buffer.

The work define the methodology to design, on the base of the Reverse Logistics Network theories, a quantitative model that simulate the mechanism in which the citizen waste recovery flow to the citizen collection center, up to the Reprocessing Center for recycling and then the disposal. The model is based on System Dynamics concepts, simulated in iThink R environment, in order to represent the PUSH/PULL hybrid logic for the management of WEEE (Waste Electrical and Electric Equipment) physical and informative flows. The model will be implemented and the simulation results will be analysed focusing on efficiency parameters, analysing the Current State Map and creating the Future State Map.

In this paper, we present a new algorithm for routing order pickers in manual warehouses and optimizing the total distance covered. The proposed approach is an adaptation of the recent water wave optimization (WWO) algorithm, a nature-inspired algorithm based on the shallow water wave theory. The algorithm is tested on a rectangular 1-block warehouse, with 12 aisles and 45 storage locations per aisle side (1080 storage locations overall). The depot is located at the bottom left corner of the warehouse. A Microsoft ExcelTM file was programmed to reproduce both the adapted WWO algorithm and to test its performance, in terms of the travel distance covered by pickers. A formal design of experiment (DOE) analysis is carried out on some of the algorithm parameters, to assess their effect on the performance observed (namely computational time and number of iterations required to reach convergence) and identify the optimal setting.

Supply chain risk management is considered a topic of increasing interest worldwide and its focus has evolved over time. The recent coronavirus pandemic (known as COVID-19) has forced business to handle a new global crisis and rapidly adapt to unexpected challenges. In an attempt to help companies counteract the pandemic risk, as well as to fuel the scientific discussion about this topic, this paper proposes a systematic literature review on risk management and disruptions in the supply chain focusing on quantitative models and paying a particular attention to highlighting the potentials of the studies reviewed for being applied to counteract pandemic emergencies. An appropriate query was made on Scopus and returned, after a manual screening, a useful set of 99 papers that proposed models for supply chain risk management. The relevant aspects of pandemics risk management have been first identified and mapped; then, the studies reviewed have been analysed with the aim of evaluating their suitability of being applied to sanitary crises. In carrying out this review of the literature, the study moves from previous, more general, reviews about risk management and updates them, starting from the lines of research that have been covered in recent years and evaluating their consistency with future research directions emerging also as a consequence of the pandemic crisis. Gaps and limitations of the existing models are identified and future research directions for pandemics risk management are suggested.

since the beginning of 2020, a new virus named COVID-19 has rapidly spread to a global pandemic. The world economy has been strongly affected and early evidence suggests that its impact has involved all the sectors and business functions. In such context, logistics activities have been severely affected by the COVID-19 pandemic because of the introduction of new strict prevention rules; moreover, purchasing behaviours of customers have changed and systems had to rapidly adapt to unexpected events. This paper aims to investigate the impact of the sanitary emergency on logistics activities. A logistic provider specialized in the food and fast moving consumer goods sector has been involved in the research in order to analyse its activities and the main changes caused by the pandemic. A quantitative survey has been conducted, combining numerical data and qualitative answers. Results confirm strong effects on some sectors and an economic loss mainly due to the new procedures adopted to face the emergency.