Riccardo Manzini

Optimization models for the dynamic facility location and allocation problem

The design of logistic distribution systems is one of the most critical and strategic issues in industrial facility management. The aim of this study is to develop and apply innovative mixed integer programming optimization models to design and manage dynamic (i.e. multi-period) multi-stage and multi-commodity location allocation problems (LAP). LAP belong to the NP-hard complexity class of decision problems, and the generic occurrence requires simultaneous determination of the number of logistic facilities (e.g. production plants, warehousing systems, distribution centres), their locations, and assignment of customer demand to them. The proposed models use a mixed integer linear programming solver to find solutions in complex industrial applications even when several entities are involved (production plants, distribution centres, customers, etc.). Lastly, the application of the proposed models to a significant case study is presented and discussed.

Environmental and economic assessment of fresh fruit supply chain through value chain analysis. A case study in chestnuts industry

In recent years, both researches and practitioners have devoted attention to environmental sustainability of supply chain (SC), while firms have modified their marketing strategies highlighting green practices in productive and logistic processes among the features of their products. These behaviours move firms to require to their suppliers the adoption of green measures and practices to reduce environmental impacts within the entire SC. This paper presents the results on an exploratory case-based research on the SC of fresh chestnuts aimed to integrate environmental concepts in the value chain approach, with a concurrent evaluation of sustainability improvements and their economic impact. Within the value chain configuration, environmental KPIs are defined for the specific case study and a logistic environmental model is developed. Within the model, an evaluation of carbon footprint for this SC is proposed, along with its possible improvements. Results include the analysis of different improvement scenarios and their comparison.

A decision-support system for the design and management of warehousing systems

The issue of material handling involves the design and operative control of warehousing systems (i.e., distribution centres), which allow matching vendors and demands, smoothing with seasonality, consolidating products and arranging distribution activities. Warehousing systems play a crucial role in providing efficiency and customer satisfaction. The warehouse design entails a wide set of decisions, which involve layout constraints and operative issues that seriously affect the performances and the overall logistics costs. This study presents an original decision-support system (DSS) for the design, management, and control of warehousing systems. Specifically, the proposed DSS implements a top-down methodology that considers both strategic warehouse design and operative operations management. The DSS can simulate the logistics and material handling performances of a warehousing system. Heuristic methods and algorithms address several critical warehouse issues, such as the order picking process, which is responsible for 55% of the overall costs in a distribution centre. The benefits due to the adoption of the proposed decision-support system are summarised as a dashboard of key performance indicators (KPIs) of space and time efficiency that allow logistics providers, practitioners, and managers as well as academicians and educators to face real-world warehousing instances and to find useful guidelines for material handling.

Framework for designing a flexible cellular assembly system

Modern manufacturing companies have to face competition in a turbulent world market that requires them to improve their operating performances according to increasingly differentiated products with shorter life cycles, low volumes and reduced customer delivery times. The aim of the present paper is to develop a conceptual framework for the simultaneous design and control of a flexible, agile reconfigurable and robust assembly system in conjunction with the analysis and optimization of product, process, system structure, material-handling devices and plant layout. An effective solution for reconfigurability and agility in assembly to order and batch-type systems is a modular semi-automatic approach based on cellular flexible facilities: modularity, automation and human skills are combined to gain the advantages of mass production. Families of parts are produced in flexible cells, i.e. groups of various machines and resources that are physically close together and process one or more families of similar parts. The proposed approach is based on a multistage iterative procedure that integrates different supporting decision techniques and tools such as design for assembly, group technologies and cellular manufacturing. An application to the optimization of a semi-automatic flexible assembly system is illustrated: the system performances of example alternative solutions are presented and compared.

Simulation performance in the optimisation of the supply chain

Purpose – Recently, material flows have been viewed as an integral part of the overall manufacturing system and a critical factor in SCM. Static approaches and theoretical models are ineffective in considering all variables and constraints involved in complex instances: these often require a lot of computing time and present poor flexibility in terms of model changes. VIS approach is a valid way to support design and management decisions in order to achieve the integrated optimisation of the whole chain, but literature does not discuss difficulties and time required in applying it, or its related costs.Design/methodology/approach – Discrete/continuous hybrid simulation tools are used in order to model and simulate several operating conditions in combination with different system configurations.Findings – The discussion of the industrial cases shows the importance of simulation in supporting decisions concerning the design and management of supply chains in their great complexity and in a stochastic compet...

Similarity-based storage allocation rules in an order picking system: an application to the food service industry

Todays distribution warehouses often need to process a far higher volume of smaller orders of multiple products which considerably increases logistics costs. They use the so-called order picking (OP) systems where products have to be picked from a set of specific storage locations by an OP process usually driven by production batches or customer orders. The OP is often very labour-intensive and its efficiency largely depends on the distance the order pickers have to travel, which therefore needs to be minimised. Minimising this distance is affected by several factors e.g. facility layout, shape of storage area, and especially the storage assignment strategy. Products that are frequently ordered together in multi-item, less than unit load customer orders should be stored near each other: this is the correlated storage assignment strategy. This study develops, tests and compares a set of different storage allocation rules based on the application of original similarity coefficients and clustering techniques. Lastly, a case study demonstrates the effectiveness of the proposed rules in minimising logistic costs.

Sustainability and quality in the food supply chain. A case study of shipment of edible oils

Purpose – Modern supply chains collect and deliver products worldwide and link vendors and consumers over thousands of miles. In the food industry, the quality of products is affected by manufacturing/processing and logistics activities, such as transportation and packaging. Specifically, transportation is likely the most critical step throughout the “food journey” from farm to fork because of the potential stresses that affect the products during shipment and storage activities. The purpose of this paper is to present and apply an original assessment of quality, safety and environmental effects due to the international distribution of food products via different container solutions. A case study that examines the shipment of edible oils from Italy to Canada demonstrates that the quality of a product at the place of consumption can be significantly affected by the use of different containers. Design/methodology/approach – A simulation-based quality assessment, combined with a life cycle and environmental ...

Estimating reliability characteristics in the presence of censored data: A case study in a light commercial vehicle manufacturing system

Abstract The reliability analysis of the critical components is the basic way to establish the efficiency of complex systems. For this issue, it is very important to select capable methods for service data collection as well as for analysis. The study introduces a framework defining a general approach for Failure Process Modeling (FPM). The paper also discusses the critical role of censored data and the need for a continuous and repetitive application of the proposed approach during the service life of systems. A case study in a light commercial vehicle manufacturing system is presented. The distributions of some reliability parameters of several critical components (i.e. reliability, hazard rate, etc.) have been estimated, repetitively during the system life, from the date of the initial installation onwards with a growing collection of time to failures. The relevant effect of the number of data, and in particular of censored data, on the robustness of reliability estimation and evaluation process is investigated.

A hierarchical procedure for storage allocation and assignment within an order-picking system. A case study

Advanced approaches to improve order-picking efficiency can significantly reduce customer response time in a supply chain system, decrease the overall logistic costs, and improve the customer service level. This paper focuses on storage allocation to properly define the right inventory level for each stock-keeping unit (SKU) and on the storage assignment problem to properly locate the SKU to the most convenient positions. The aim of this paper is to present a systematic hierarchical top-down procedure that allows the combining of sequential decision steps concerned with allocation and assignment issues. The proposed procedure is applied to a case study, and the results obtained from a what-if analysis are presented.

Framework for designing and controlling a multicellular flexible manufacturing system

In the economic environment of recent years, management in modern organisations has had to make flexible responses to constantly changing new product lines and product varieties. Flexibility, which is the capability of a system to adapt to changes made to it, is becoming one of the most critical factors for success in the manufacturing industry. In this context, the design and the management of flexible manufacturing systems (FMSs) are crucial and important issues. This paper presents an innovative, integrated, and optimising iterative process which supports the planning and control of a multistage and multicellular FMS. It is based on the simultaneous application of simulation tools and heuristic techniques. The proposed framework has been applied to the optimisation of a manufacturing system from the Italian automotive industry. The effectiveness of simulation techniques, aimed at the strategic and operative decision-making process, emerges.