Riccardo Accorsi

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.

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 ...

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.

Operational planning models for distribution networks

The design and optimisation of a logistic network deals with a wide set of decisions, e.g. the determination of the best location and capacity of the different logistic facilities (production plants, distribution centres, transit points, wholesalers, etc.), the allocation of the product demand coming from customers in presence (or absence) of fractionable flows of material, the determination of the best transportation mode (truck, rail, etc.) as well as loading and routing of vehicles. These decisions involve multiple stages of a distribution network: customers-regional distribution centres (RDC), RDCs-central distribution centres (CDC) and CDCs-production plants and sources, in presence of multiple products and the variable time (i.e. time-dependent product demand and flows of material). This paper presents a top-down methodology that joins the strategic planning, the tactical planning and the operational planning of distribution networks with a special focus on the development of effective heuristic methods to face the vehicle routing problem. Original models and heuristic algorithms for the operational planning are illustrated. The impact of the strategic and tactical decisions on the performance of the operational planning is evaluated by the application of the proposed hierarchical approach to two realistic case studies. Obtained results are illustrated in a what-if experimental analysis conducted on multiple problem settings and realistic scenarios.

The scheduling of maintenance. A resource-constraints mixed integer linear programming model

This paper presents and applies an original MILP model for scheduling preventive maintenance of complex machines made of hundreds of components.This model is cost-based, reliability-based and time resource constraints.Effective for real applications with a large number of tasks, service orders and spare parts.Applied to a significant case study in a what-if environment. The scheduling of preventive maintenance is crucial in reliability and maintenance engineering. Hundreds of parts compose complex machines that require replacement and/or repairing. Maintenance involves the machine vendor (1), the machine user (2) and the service maintenance provider (3). The vendor and the maintenance service provider have to guarantee a high level of availability and productivity of the machines and maintain their down-time at a minimum even though they are installed worldwide and usually far from the vendors headquarters and/or the locations of the providers regional service offices. Moreover, many companies have great profits from maintenance and spare parts management.This study aims to illustrate an original mixed integer linear programming (MILP) model for the cost-based, reliability-based and resource-constraints scheduling of preventive maintenance actions. The model minimizes the total cost function made of spare parts contributions, the cost of the execution of the preventive actions and the cost of the additional repair activity in case of unplanned failure. The cost of the personnel of the producer and/or the maintenance service provider is also included. Finally, the paper presents a case study in a what-if environment demonstrating the effectiveness and the novelty of this study in real and complex applications.

Travel time models for deep-lane unit-load autonomous vehicle storage and retrieval system (AVS/RS)

Autonomous vehicle storage and retrieval systems use vehicles that move horizontally along rails within the storage racks, while vertical movements are provided by lifts. The solution proposed in this paper addresses a particular system configuration that works with multiple deep storage lanes that are widely used in the food and beverage industry, characterised by large volumes of products of limited variety. The generic deep lane is single item, i.e. one stock keeping unit, and single batch, i.e. one production lot, thereby affecting the performance of the system in terms of storage capacity utilisation and throughput. Determining the number and depth of the lanes is crucial to aid the design and control of such a storage system. The aim of this paper was to support the design of AVS/RSs though a set of original analytic models for the determination of the travelled distance and time for single-command and dual-command cycles given alternative layout configurations. The models are validated by simulation and exemplified with a real-warehousing case study. The paper presents useful guidelines for the configuration of the system layout including the determination of the optimal shape ratio and the length of the lanes.

Plant design and control in food service industry. A multi-disciplinary decision-support system

Abstract Every day, thousands of pupils, students, employees, and hospital patients eat food outside their homes that is cooked far from the place of consumption. The food service industry is responsible for supplying this food to schools, hospitals, nurseries, as well as to company canteens. The design, control, and management of food service operations is challenging given the complexity of such multiple facility production networks and entails multidisciplinary perspectives and competences. Both production and logistics operations play crucial roles and significantly affect the service performance as long as food products are prepared within a facility, and as long as they are distributed to multiple consumption sites. Hence, there are many planning decisions (e.g. the definition of the production facility location, the allocation of task to resources and the scheduling of production jobs), that are handled at different stages by different actors, who often decide based on their own practical experience and barely adopt integrated decision-support systems. A review of the literature shows that there is no integrated approach to support the design of food service production facilities, known as centralized kitchens (CEKIs). To facilitate such integration and assist food service managers to adopt quantitative and data-driven design approaches, this study proposes an original computer-based multidisciplinary decision-support tool for the design and configuration of a CEKI. The proposed tool aids decisions taken by multiple actors simultaneously through a set of interfaces driven by quantitative data that follow the logistical flow of materials throughout the CEKI (1), assesses performance indicators in a multidisciplinary dashboard (2), and implements what-if, multiple scenario analyses based on simulations (3). Graphical interfaces are designed to facilitate communication between the decision makers and the integration of data-driven analyses. The design of a new CEKI is used as a testbed for the decision-support tool. The real-world example highlights the interdependencies between issues and decisions and showcases how computer applications facilitate decision-making and improve communication between managers.

A Supporting Decisions Platform for the Design and Optimization of a Storage Industrial System

In a recent survey the consulting company AT Kearney (ELA/AT Kearney survey 2004) states that there are more than 900,000 warehouse facilities worldwide from retail to service parts distribution centers, including state-of-art, professionally managed warehouses, as well as company stockrooms and self-store facilities. Warehouses frequently involve large expenses such as investments for land and facility equipments (storage and handling activities), costs connected to labour intensive activities and to information systems. Lambert et al. (1998) identify the following missions:  Achieve transportation economies (e.g. combine shipment, full-container load).  Achieve production economies (e.g. make-to-stock production policy).  Take advantage of quantity purchase discounts and forward buys.  Maintain a source of supply.  Support the firm’s customer service policies.  Meet changing market conditions and again uncertainties (e.g. seasonality, demand fluctuations, competition).  Overcome the time and space differences that exist between producers and customers.  Accomplish least total cost logistics commensurate with a desired level of customer service.  Support the just-in-time programs of suppliers and customers.  Provide customers with a mix of products instead of a single product on each order (i.e. consolidation).  Provide temporary storage of material to be disposed or recycled (i.e. reverse logistics).  Provide a buffer location for trans-shipments (i.e. direct delivery, cross-docking). Bartholdi and Hackman (2003) conversely recognize three main uses:  Better matching the supply with customer demands Nowadays there is a move to smaller lot-sizes, point-of-use delivery, high level of order and product customization, and cycle time reductions. In distribution logistics, in order to serve customers, companies tend to accept late orders while providing rapid and timely delivery within tight time windows. Consequently the time available for order picking becomes shorter.