Salvatore Digiesi

A loss factor based approach for sustainable logistics

Logistics plays a key role for industries since it reveals a critical function designed and managed to pursue economic goals. A large amount of literature is available, providing models which can be used to minimise logistic costs. However, models usually neglect externalities, i.e. social and environmental costs that have to be considered in the framework of sustainable manufacturing. In this article, the authors propose an inventory model to support decision making in means of transport selection and order lot sizing (sustainable order quantity) which minimise both logistic and environmental costs. Dependency of logistic and environmental costs is shaped as functions of the ‘loss factor’, a parameter adopted to classify means of transport based on loss in transport energy. Time and cost constraints as well as the actual means of transport availability reduce the domain of theoretical solutions and limit the set of feasible ones. When there are no feasible solutions, three different strategies are identified and discussed to support logistic management in meeting sub-optimal feasible logistic performance under time, cost and means of transport constraints.

A Sustainable Order Quantity Model under Uncertain Product Demand

Abstract The Economic Order Quantity (EOQ) model is one of the most known classical continuous review inventory model based on the trade-off between holding and order costs. In actual logistic systems, transport costs play a key role, and in case of stochastic variability of product demand and/or supply lead time, a safety stock is required. Transport and safety stock costs affect the solution of the lot size problem. Recently, wide attention is being paid to sustainable manufacturing and in particular on negative effects of transport. Transports are the main source of air pollutant emissions in EU and are expected to increase in magnitude in the future. Costs evaluations of transport emissions are defined in EU documents based on Kyoto protocol. When transport environmental costs are considered in the logistic cost function a new lot-sizing problem can be defined. In (Digiesi, Mossa and Mummolo 2012), the Sustainable Order Quantity (SOQ) analytical model is proposed aiming at identifying optimal lot-size and transport means which minimize the logistic and environmental costs in case of a deterministic product demand. In this paper, the authors propose an SOQ model in case of stochastic variability of product demand. Analytical model solutions rely on sustainable (in terms of both logistic and environmental costs) order size, transport means and safety stocks. Results obtained in a full case study from automotive supply chain case study are presented.

Sustainable Order Quantity of Repairable Spare Parts

Abstract In the last few years companies and researchers have focused their attention on the sustainable issues of supply chain management. In spare parts (SPs) research, traditionally focused on inventory modeling, supply chain aspects have become of relevant interests. Many contributions could be found in scientific literature about logistics of spare parts, but there is a lack of attention on the sustainable issues. In this paper, authors give a contribution to the concept of sustainable management of spare parts, by defining a spare parts logistic model. The model considers the environmental impacts and benefits related to the possibility of repairing failed parts rather than purchasing new ones. It aims at identifying the optimal means of transport, as well as the optimal SP order quantity minimizing the global logistic costs function in which economic and environmental costs of both the options of repairing and purchasing SPs are considered. The capability of the model has been tested with reference to a numerical example based on real data of a leader manufacturer of bearings.

Minimizing Carbon-Footprint of Municipal Waste Separate Collection Systems

Environmental performance of municipal waste management systems plays a key role in the so called smart cities performance. The authors propose a reference framework for public decision-making in optimizing municipal waste separate collection systems. A Mixed Integer Nonlinear Programming (MINLP) model is built up to set the collecting system (CS) and the optimal level of collection of each fraction. The goal is to minimize carbon footprint of the whole CS. The model is applied to a full-scale case study. Results obtained stress out the effectiveness of the model. Moreover the Environmental Efficiency Effort index is introduced to test the model solution evaluating the attitude of citizens in participating and improving waste separate collection.

Optimal Break and Job Rotation Schedules of High Repetitive – Low Load Manual Tasks in Assembly Lines: an OCRA – Based Approach

Abstract Human labor still plays a crucial role in many work contexts. However, increases in production rate require increases in human workloads. The authors propose two integer programming models aiming at finding both optimal break and job rotation schedules in work-environments characterized by low load manual tasks with high frequency of repetition. In such a work environment a major risk consists of work-related musculoskeletal disorders. Workload risk and acceptability are evaluated by the OCRA index (ISO 11228-3:2007). Models proposed are applied to an assembly line from the automotive industry. Results obtained revealed the effectiveness of the models as they proved to be adequate tools to jointly address the reduction and balancing of human workloads among employees, which are consistent with acceptable workload limits and required production levels.

Externalities reduction strategies in last mile logistics: A review

In this paper a review of recent contributions in scientific literature on the last mile logistics is presented. The increase in freight transport and the actual growing trends are responsible, in the urban areas, of a critical increase of congestion, air pollution, noise and others externalities that involve the major cities in the world. New technologies and organizational strategies allow handling in a more efficient way the last mile delivery in urban areas. Papers that contribute significantly and with original proposal in reducing externalities in urban logistics are analysed in this work.

Internalisation strategies of external costs of transport for a sustainable logistics

Transport is a priority issue for a sustainable development. The European Commission planned to implement a full and mandatory internalisation of the transport external costs within the 2020 (EU, 2011). Traditional inventory models, however, minimise logistics costs neglecting externalities. The aim of this paper is to evaluate the social and environmental benefits of the internalisation of the external costs in the inventory management problem. The sustainable order quantity model (Digiesi et al., 2012) has been adopted here in order to identify the optimal lot-size and transportation mean minimising logistic and external costs of transport. A sensitivity analysis has been performed in order to investigate the effects of different internalisation strategies on the solution of the inventory problem. In order to evaluate the effectiveness of the proposed strategies, they have been tested on a real case study.

A model-based Decision Support System for multiple container terminals hub management

Paper aims: To develop a model-based Decision Support System (DSS) that allows identifying the best strategy of the inter-/intra-terminal flows of the containers in order to increasing the performance of the hub under economic and environmental perspective. Originality: The adoption of a dry port can effectively solve the congestion problem of a terminal only if an integrated sustainable solution (dry port location and container strategy storage) is identified. Research method: The model is based on a heuristic computational algorithm for non-linear programming. Main findings: The application of DSS to a full-scale numerical case show the model capabilities in identifying the optimal logistic strategies ensuring a low CF and in optimizing the cost due to transport activities. Implications for theory and practice: It is possible to identify different strategies allowing to obtain an eco-friendly solution reducing, at same time, the costs for a given number of containers to be handled.

Electric and LPG forklifts GHG assessment in material handling activities in actual operational conditions

The aim of the present paper is to give a contribution on the debate regarding the environmental impact, in terms of GHG emissions, of material handling activities performed with LPG or electrically powered forklift trucks. A model of the operations performed by the trucks, based upon a decomposition approach into elementary steps, is illustrated and data drawn from technical sheets are employed, in order to evaluate the required times and the associated energy consumption. Recharging cycles of batteries and the emissions associated with recycle / reconditioning process at their end of life are also taken into account. Comparisons are then carried out for a reference storage of units. The results obtained lead to conclude that electrically powered trucks are always advantageous over LPG powered ones with the same rated load capacity in the examined range and under the stated assumptions, both under the environmental aspect and the economic point of view, with the assumed figures of the cost of energy.

A Nonlinear Integer Programming Model for Warehousing Sustainable Logistics

The warehouse management problem is a critical issue in Operation Management. In modern competitive market, many firms are automating their basic warehouse activities in order to be cost effective. However, traditional mechanized warehousing systems (MWS) still represent the 75 % of the overall installations. In MWS, forklifts are adopted for the load handling. The adoption of efficient “internal logistic strategies” could help in reducing time required and costs of warehousing activities. In recent years, many firms adopted green supply chain practices (GSCP) in order to improve their environmental performances while also achieving economic goals (Wu et al. 2015). Furthermore, in planning Smart City logistics, warehousing in port or railway station storage areas is being receiving wide attention since they contribute effectively to a sustainable development of modern cities. Under this perspective, an optimal “internal logistic strategy” allowing to jointly minimizing jointly costs and environmental impacts of warehousing activities has to be adopted. The aim of this study is to develop a Nonlinear Integer Programming Model to solve a storage location assignment problem (SLAP) for optimizing the environmental performance of the internal logistic activities in a warehouse. Suitable storage strategies are identified on the basis of the type of the forklifts adopted (internal combustion or electric engine equipped) as well as the sizes and the weight of the loads to be handled.