Giorgio Mossa

Production planning of a multi-site manufacturing system by hybrid modelling: A case study from the automotive industry

Abstract The paper deals with lot sizing and scheduling problem (LSSP) of a multi-site manufacturing system with capacity constraints and uncertain multi-product and multi-period demand. LSSP is solved by an hybrid model resulting from the integration of a mixed-integer linear programming model and a simulation model. The hybrid modelling approach is adopted to test a local as well as a global production strategy in solving the LSSP concerned. The model proposed is applied to a supply chain of a multi-site manufacturing system of braking equipments for the automotive industry. Solutions obtained by the hybrid model under the local or the global production strategy are compared with an actual reference production plan. The approach could help decision making in adopting a cooperative, rather than competitive, production strategy.

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.

Modelling dynamics of a supply chain under uncertainty: a case from the automotive industry

The authors investigate a three-stage supply chain of a multinational firm in the automotive components industry. Factories, located in Italy, carryout the manufacturing process of components for braking equipment. The first two manufacturing sites provide the final assembly site with components for original equipment (OEC); they also produce components for the aftermarket (AMCs). The demand for OECs is dynamic and is deterministically known on a one-year horizon. On the other hand, the demand for AMCs is uncertain and is distributed according to probability density functions. To face such complexity in evaluating the supply chain performance, a dynamic and stochastic simulation model is proposed. Two different scenarios are investigated according to whether the manufacturing sites are onsidered as independent business units or as units that obey strict production requirements of the supply chain. The results obtained confirm the effectiveness of the model, which reveals a suitable tool for tactical/strategic decision making.

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.

Increasing public healthcare network performance by de‐hospitalization

Purpose – The aim of this paper is to support public decision‐makers in a local healthcare agency (LHA) in evaluating the effects of different de‐hospitalization strategies and the potential for outsourcing clinical services.Design/methodology/approach – The approach adopted is based on the “patient pathway” perspective. Starting from the identification of specific care pathways, all the feasible care paths in a given LHA in Italy are investigated in order to evaluate the practicability of the de‐hospitalization of some phases with a particular focus on co‐ordination of hospitals and territorial services. A heuristic approach based on discrete‐event simulation modelling is proposed. The methodology and the simulation model have been validated with reference to field data derived from a full‐scale case study carried out within a LHA in southern Italy.Findings – The results show where, in terms of care pathways, de‐hospitalization is practicable, valuable in terms of better resource utilization, and eligibl...

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.

Spare parts inventory reduction: A multi-attribute approach

Abstract The paper aims to define a multi-attribute model allowing to re-design spare parts (SPs) inventory. The model helps in evaluating the inventory configuration compliant with both production and storage costs requirements. The model is based on SPs attributes to be considered critical for a production system. For each SP a reduction index is computed as a function of the attributes values expressed by the judgments of different decision-makers. A transform function is defined to convert reduction indexes into SPs stock reduction quantities. The transform function is consistent with a set of reduction policies to be adopted on the base of internal (i.e. system utilization) and external (i.e. supply quality) variables affecting system behaviour. The model has been tested and validated on a catalogue of a SPs supplier of an automotive components company. Due to the crisis of the automotive sector of the last two years, the management of the plant shifted the focus from high technical availability level of production system to the reduction of production costs and SPs stock in the local warehouse. Data collection and data mining required for SPs inventory reduction by traditional management policy revealed as time and resource consuming task. Results obtained by the proposed approach revealed the effectiveness of the model in reducing SPs inventory, as well as a reduced effort in carrying out the analysis.