Supply Lead Time Uncertainty in a Sustainable Order Quantity Inventory Model

Abstract Transport plays a key role in inventory management since it affects logistic costs as well as environmental performance of the supply chain. Expected value and variability of supply lead time depend on the transportation means adopted, and influence the optimal values of order quantity, reorder level, and safety stock to be adopted. Fast transportation means allow reducing expected value of the lead time; they are characterized by the highest costs of externalities (i.e. air pollutant emission, noise, congestion, accidents). On the contrary, slow transportation means require high inventory level due to large order quantity; in this case costs of externalities tend to decrease. The Sustainable Order Quantity (SOQ) [1] allows identifying optimal order quantity, reorder level, safety stock as well as transportation means which minimize the sum of the logistic and environmental costs in case of stochastic variability of product demand. In this paper, the authors propose a new SOQ analytical model considering stochastic variability of supply lead time (LT). A solution procedure is suggested for solving the proposed model. The approach is applied to a real industrial case study in order to evaluate the benefits of applying it if compared with the traditional one

An analytical framework for assessing cognitive capacity and processing speed of operators in industry 4.0

Abstract The fourth industrial revolution introduced a new paradigm in manufacturing systems. The digital network is at the basis of the smart manufacturing and the physical context is strictly related to the artificial intelligence. This new manufacturing context drastically changed the role of the operator since the increasing adoption of innovative devices in manufacturing process modified the work activities and the operator is employed in more cognitive than physical tasks. Therefore, the purpose of this paper consists in developing an analytical framework to assess the human cognitive capacity occupancy and the human processing time of correct information known as the quality performance. The analytical framework presented allows to assess the human mental workload imposed by the task and how the processing speed of correct information changes when quality performance varies

Strategic Energy Planning of Residential Buildings in a Smart City: A System Dynamics Approach

Buildings are the largest urban energy consumers, but their impact can be largely cut back by improving efficiency. Policy-making plays a crucial role in harmonizing national and local incentive schemes. The authors analyse variables related to energy consumption, then propose a simulation model based on System Dynamics applied to a medium- sized Italian city. The model allows the testing of “what-if” scenarios and analysis of the results of implementing energy efficiency policies. Results stress the importance of a holistic view of urban energy processes. Simulation trends provide essential information for the city’s future energy and carbon emission profiles, helping policy-makers to achieve their goal

Supporting Circular Economy through Use-Based Business Models: The Washing Machines Case

Abstract The circular economy paradigm is being widely studied as a possible path to a sustainable development, decoupling economic growth from material consumption and environmental impacts. The introduction of new business models, based on use rather than ownership, has been identified as one of the possible enabling actions for the implementation of circular economy strategies. Thus, product-service systems (PSS) can represent a viable way for companies and customers to switch from a linear to a circular scheme, keeping together the advantages of a customer-oriented offer to those of dematerialization. In this work, an example of innovative, circular business model for the large appliances sector is proposed, based on a PSS and a closed-loop supply chain. A context study, supported by a deep literature analysis, is performed to identify the main changes involved in the transition from a traditional to a circular supply chain in the sector, as well as the main impacts on the actors involved, through causal loop diagrams. The study is a first step for the realization of a system dynamics model, for a further research on impact assessment

ANN Modelling to Optimize Manufacturing Process

Neural network (NN) model is an efficient and accurate tool for simulating manufacturing processes. Various authors adopted artificial neural networks (ANNs) to optimize multiresponse parameters in manufacturing processes. In most cases the adoption of ANN allows to predict the mechanical proprieties of processed products on the basis of given technological parameters. Therefore the implementation of ANN is hugely beneficial in industrial applications in order to save cost and material resources. In this chapter, following an introduction on the application of the ANN to the manufacturing process, it will be described an important study that has been published on international journals and that has investigated the use of the ANNs for the monitoring, controlling and optimization of the process. Experimental observations were collected in order to train the network and establish numerical relationships between process-related factors and mechanical features of the welded joints. Finally, an evaluation of time-costs parameters of the process, using the control of the ANN model, is conducted in order to identify the costs and the benefits of the prediction model adopted

Cleaner Production Initiatives in a DieselEngines Factory

This paper presents a case study conducted in a Diesel engines manufacturer, which ad-opted a Cold Test machine to perform the final check of engines in the assembly line. The overall aim of this investigation was evaluating the economic and environmental advantages obtained by the adoption of the Cold Test machine. The results showed cost saving of USD 558,012.67 per year. The investment required, USD 2.1millions, returned in three years and ten months. The environmental assessment identified the reduction of the mass intensity per abiotic, biotic, water and air compartments, total of 178,420,306.06 kg resources conserva-tion per year