Susana Relvas

Design and planning of supply chains with integration of reverse logistics activities under demand uncertainty

In this paper, a mixed integer linear programming (MILP) formulation is developed for the design and planning of supply chains with reverse flows while considering simultaneously production, distribution and reverse logistics activities. It is also considered products’ demand uncertainty using a scenario tree approach. As main goal the model defines the maximization of the expected net present value and the results provide details on sizing and location of plants, warehouses and retailers, definition of processes to install, establishment of forward and reverse flows and inventory levels to attain. The model is applied to a representative European supply chain case study and its applicability is demonstrated.

Alexandre Dolgui and Jean-Marie Proth, Supply Chain Engineering - Useful Methods and Techniques , Springer-Verlag (2010) 541 pp., ISBN: 978-1-84996-016-8

Supply Chain Engineering considers how modern production and operations management (POM) techniques can respond to the pressures of the competitive global marketplace by integrating all activities in the supply chain, adding flexibility to the system, and drastically reducing production cost. Several POM challenges are answered through a comprehensive analysis of concepts and models that assist the selection of outsourcing strategies and dynamic pricing policies. The ramifications of these topics are discussed from local to global perspectives. Supply Chain Engineering also presents inventory control policies, radio frequency identification (RFID) technologies, flexible and re-configurable manufacturing systems, real-time assignment and scheduling methods, new warehousing techniques. In addition, a significant part of the book is devoted to: lean manufacturing, line balancing (assembly lines, U-lines, and bucket brigades), and dynamic facilities layout approaches. Explanations are given using basic examples and detailed algorithms, while discarding complex and unnecessary theoretical minutiae. Moreover, all the examples have been carefully selected with a view to eventual industrial application. Supply Chain Engineering is written for students and professors in industrial and systems engineering, management science, operations management, and business. It is also an informative reference for industrial managers looking to improve the efficiency and effectiveness of their production systems.Supply chain management (SCM) is a concept that addresses the supply, sourcing, procurement, conversion and logistics activities, using collaboration and integration along the supply channel and is crucial to any company in the fierce context the world and its economy are living nowadays. This book contributes to lessen the gap between academic methods and business activities by providing simple and systematic methods for a series of supply chain problems faced by real world decision makers and managers. The book accomplishes a triple objective for the reader: to provide the basic concepts and representation models for identified problems, to provide an actual view of businesses and to provide practical strategies to include market, competition and external context issues in management decisions.

Metrics for Bullwhip Effect Analysis

A bullwhip measurement system based on a two-criterion assessment—‘internal process efficiency’ and ‘customer service level’—is developed in this paper. The framework is designed to assess both individual (single member) and systemic (whole supply chain) performances. Data collection and calculation methods, update and monitoring mechanisms, as well as related procedures for each metric used, are detailed. A comparative analysis with a recent work by Barlas and Gunduz is performed, showing that the adoption of the proposed performance measurement system can help academics and practitioners to better understand, study and avoid the bullwhip effect. Such analysis also provides evidence on the relevance of considering when analysing the bullwhip effect in supply chains, the ‘customer importance’ aspect that is often forgotten in the published literature.

The effect of Inventory Record Inaccuracy in Information Exchange Supply Chains

The goal of this paper is to quantify the impact of Inventory Record Inaccuracy on the dynamics of collaborative supply chains, both in terms of operational performance (i.e. order and inventory stability), and customer service level. To do so, we model an Information Exchange Supply Chain under shrinkage errors in the inventory item recording activity of their nodes, present the mathematical formulation of such supply chain model, and conduct a numerical simulation assuming different levels of errors. Results clearly show that Inventory Record Inaccuracy strongly compromises supply chain stability, particularly when moving upwards in the supply chain. Important managerial insights can be extracted from this analysis, such as the role of ‘benefit-sharing’ strategies in order to guarantee the advantage of investments in connectivity technologies.

Risk Management Framework for the Petroleum Supply Chain

Abstract Complex plants and investments are commonplace in the Petroleum Supply Chain (PSC), known for its highly automated infrastructures and processes. Expensive equipment items like drilling rigs, offshore platforms, oil tankers, refineries, pipelines, petroleum depots and transport equipment are critical to this industry. The petroleum supply chain appears as a significant risk and high impact industry at the micro and macro economic level. Although, risk management bears prime importance for this industry, there is notorious absence of quantitative modeling. This paper introduces the relevance of a systematic approach for the identification, quantification and mitigation of risk and presents a practical framework for risk management. A PSC example is used to demonstrate its utilization and the resulting information identifies modeling data for a PSC risk management tool.

Supply Chain Risk Management Review and a New Framework for Petroleum Supply Chains

Supply Chains have significantly increased in size and complexity due to supplier, producer and customer globalization. The quest for business efficiency has resulted in the current paradigm of lean organizations, exposing high vulnerability to disruptions and uncertainties. Supply Chain Risk Management (SCRM) has surfaced as a high potential field to foster business sustainability, flexibility and resilience. The Petroleum Supply Chain (PSC), a highly automated, investment intensive, and financial risk prone industry sees keen interest in uncertainty mitigation. The current paper develops a hierarchical SCRM framework and presents a classified review of the extant SCRM literature. The investigation then focuses on the petroleum supply chain risk management (PSC-RM), reviews the PSC and the process industry developments, develops a hierarchical RM methodology, identifying research directions and financial offerings for the PSC-RM implementation.

Pipeline scheduling and distribution centre management—A real-world scenario at CLC

Abstract Competion is growing every day around petroleum industry, and more specifically in the management of the respective supply chains. Technology has been one of the main tools where development and benefits have been obtained. This work develops the basis of a decision support tool that relies on the development of a MILP model to answer the real world scenario of CLC—Companhia Logistica de Combustiveis, a company that receives petroleum derivatives from a refinery through a pipeline and distributes them in the central area of Portugal. The model combines the pipeline operation with the end-of-pipe distribution centre management. The formulation relies on continuous time and pipeline volume representations. Solutions are obtained recurring to standard B&B techniques.

Resilience assessment of supply chains under different types of disruption

Abstract In the present work the design and planning of resilient supply chains is addressed in the presence of uncertain demands. A Mixed Integer Linear model is applied to both forward and closed-loop supply chains, and the systems behavior analyzed when facing several types of disruption. This analysis is made considering two situations: the disruption occurs either with certainty or with a probability associated to its occurrence. This last case incorporates both sources of uncertainty, meaning uncertainty in demands and uncertainty in the disruptions occurrence. In addition to the economic evaluation, the performance of the networks is compared using six different indicators that encompass network design indicators, such as node and flow complexity, density and node criticality, and two operational indicators, customer service level and investment. These indicators are analyzed with the objective of finding out which characteristics a manager should consider when designing and planning resilient supply chains.

Modeling Integrated Biorefinery Supply Chains

Abstract This paper addresses an integrated biorefinery supply chain analysis in order to identify the critical factors that can contribute to such system effective modeling. Accordingly, a general mixed integer linear programming (MILP) formulation is developed to support the design of an integrated biorefinery supply chain. The model aims to attain the optimal supply chain configurations from many possible alternatives depending on (i) a large portfolio of biomass sources with distinct physical and chemical characteristics and with different possible locations for its supply; (ii) diverse storage types, with or without pre-processing technologies, and locations; (iv) different transportation modes for every material flows; (iv) different processing technologies to attain a large portfolio of biobased products as well as capacities and locations and (v) manage a large portfolio of end products to be sent to different markets. The model is supported by a database built in Excel in order to allow the application of the model to specific situations and be applied as a decision support system.

Downstream Petroleum Supply Chain Planning under Uncertainty

Abstract Design and planning of petroleum supply chains (PSC) present significant opportunity as financial crunches and variability in crude oil prices continue augmenting volatility among the petroleum product prices, costs, margins and demand. To deal with this challenge, we present a stochastic mixed integer linear program (MILP) that maximizes the expected net present value (ENPV) while simultaneously minimizing a risk measure the conditional value-at-risk (CVaR) under demand uncertainty. The bi-objective MILP model determines the design decisions relating to installation, sizing and operation of infra-structures, the fair price strategic cost and tariffs and tactical decisions concerning periodic depot and route product affectations and inventory levels. Pareto optimal solutions are obtained for the retrofit network design of the Portuguese PSC, wherein computational results are presented and identified opportunities for further research.