Efficiency & sustainability model to design and manage two-stage logistic networks

The distribution and storage efficiency together with the environmental sustainability are mandatory targets to consider when designing and managing modern supply chain (SC) networks. The current literature continuously looks for quantitative multi-perspective strategies and models, including and best balancing such issues that often diverge. This paper presents and applies a bi-objective optimization model to best design and manage two-stage logistic networks looking for the best trade-off between the SC stock level and the building and distribution environmental impact. The existence of good balance confirms the possibility to reduce the average SC stock level without a relevant increase of the emissions due to frequent replenishments

Reliability Assessment of a Packaging Automatic Machine by Accelerated Life Testing Approach

Industrial competitiveness in innovation, the time of the market introduction of new machines and the level of reliability requested implies that the strategies for the development of products must be more and more efficient. In particular, researchers and practitioners are looking for methods to evaluate the reliability, as cheap as possible, knowing that systems are more and more reliable. This paper presents a reliability assessment procedure applied to a mechanical component of an automatic machine for packaging using the accelerated test approach. The general log-linear (GLL) model is combined based on a relationship between a number strains, in particular mechanical and time based. The complete Accelerated Life Testing - ALT approach is presented by using Weibull distribution and Maximum Likelihood verifying method. A test plan is proposed to estimate the unknown parameters of accelerated life models. Using the proposed ALT model, the reliability function of the component is evaluated and then compared with data from the field collected by customers referring to 8 years of real work on a fleet of automatic packaging machines. The results confirm that the assessment method through ALT is effective for lifetime prediction with shorter test times, and for the same reason it can improve the design process of automatic packaging machines

dynamic design and management of reconfigurable manufacturing systems

Abstract This research proposes an approach to design and to manage Cellular Reconfigurable Manufacturing Systems (CRMSs) from a multi-product and multi-period perspective. The production environment consists of multiple cells of machines equipped with Reconfigurable Machine Tools (RMTs) made of basic and auxiliary custom modules to perform specific tasks. The approach acts into two steps; the former is the machine cell design phase, assigning machines to cells, the latter is the cell loading phase, assigning modules to each machine and cell. The goal is to guarantee the economic sustainability of the manufacturing system by exploring how to best balance the part flow among machines already equipped with the required modules and the effort to install the necessary modules on the machine on which the part is located

Integration of single and dual command operations in non-traditional warehouse design

Abstract Non-traditional warehouses rise as effective solutions to shorten the travelled distances to store and retrieve unit loads, adding aisles crossing the parallel racks. Multiple warehouse configurations are proposed by the literature discussing the enhancements toward standard layouts. In previous contributions, the authors introduced the diagonal cross-aisle model, concluding about its positive impact on the handling performances under single command operations. This paper extends the previous works, integrating dual command operations, through an original analytic model supporting the design of non-traditional warehouses with a couple of symmetric straight diagonal cross-aisles and random storage assignment strategy. The closed-form expressions to compute the expected cycle travel distances are provided, optimising the aisle position. An industrial case study applies the model, getting distance savings ranging from 11 to 17%, compared to standard layout and further considering the loss of storage space due to the presence of the additional aisles

A cross‐sectorial review of industrial best practices and case histories on Industry 4.0 technologies

Industry 4.0 (I4.0) was introduced in 2011, and its advanced enablers strongly affect industrial practices. In the current literature, while several papers offer general reviews on the topic, contributions exploring the evidences coming from the implementation of I4.0 in multi-sector Small and Medium Enterprises (SMEs) and large enterprises are few and expected. To address this gap, a comprehensive review of the main I4.0 enabling technologies is conducted, focusing on implementation experiences in companies belonging to different sectors. Forty (40) real case studies are analyzed and compared. The results show that 63% of the identified applications involve large enterprises in the transport sector, that is, automotive, aeronautics, and railway, adopting a structured set of enabling technologies. SMEs engaged in I4.0 projects primarily belong to the mechanical engineering sector, and 37% of such projects deals with the preliminary feasibility analysis of introducing a single enabling technology. Conclusions and trends guide researchers and practitioners in understanding the implementation level of I4.0 technologies

towards optimum energy utilization by using the inverters for industrial production

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toward a real time reconfiguration of self adaptive smart assembly systems

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prognostic health management of production systems new proposed approach and experimental evidences

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Thermal comfort prediction of aged industrial workers based on occupants' basal metabolic rate

The increasing workforce ageing brings benefits and challenges in industrial structu- res. Industries consider aged workers as essential resources thanks to their experience and skills. Conversely, the aged workers’ progressive functional and cognitive decline reduce their tolerance to industrial environmental conditions, negatively impacting performance. In particular, after age 30, there is a progressive inefficiency in the physiological response to temperature changes. Therefore, thermal discomfort conditions have a worse impact as the workers’ age increases. The Predicted Mean Vote (PMV) methodology is conventionally used to predict the human sensation of thermal comfort on a seven-point thermal sensation scale. Such methodology does not take account of progressive decline in thermoregulation capacity with age. This paper aims to fill this gap by proposing an analytic model for the prediction of thermal comfort. The Metabolic rate (M) parameter in the PMV equation is calculated from the Harris-Benedict equations revised by Mifflin and St Jeor (1990) for the Basal Metabolic Rate (BMR), including the age factor for a more accurate evaluation of the workers’ thermal sensation. The aim is to safeguard the aged workers’ health and well-being to enhance their performance during work

implementation of reconfigurable manufacturing in the italian context state of the art and trends

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