Planning production and logistics at a major sugar company in Argentina



Similar documents
School of Management and Languages Capacity Planning

Argentine Commercial Farm/Ranch Management Information Systems: Design, Capabilities, Costs and Benefits. Abstract:

ARGENTINE NON GMO SOYBEAN CHAIN

Opportunities and Challenges in the Design and Analysis of Biomass Supply Chain

Linear Programming Refining Transportation

Supply Chain Comparison. COEE Project 1

Refinery Planning & Scheduling - Plan the Act. Act the Plan.

Ask the groups to read their cards and give them 5 10 minutes to think about their roles. How do they feel about it? Is everything clear?

Washington State Industry Outlook and Freight Transportation Forecast:

Model, Analyze and Optimize the Supply Chain

Supply chain planning of harvest operations and transportation after the storm Gudrun

Business Solutions that Create Value for Aluminium Producers

GLOBAL AND CHINESE 3D PRINTING INDUSTRY, 2016 MARKET RESEARCH REPORT

Supply Chain Management-A Quality Improving Tool in Process Industries

INTEGRATED SUPPLY CHAIN PLANNING IN NETWORK OPTIMISATION

China and the WTO: Implications for Grain Trade. Dr. Thomas I. Wahl IMPACT Center Washington State University

Improving Profitability by an Integrated, Collaborative Approach to Supply Chain Optimisation and Management

Blending petroleum products at NZ Refining Company

CSCMP Level One : Cornerstones of Supply Chain Management. Learning Blocks

Supply Chain Design and the effects on shipping

CPCS Supply Chain Review. Eastern Canada Logistics Study By CPSC November 2012

Analysis of the determinants of prices and costs in product value chains

Optimizing Supply Chains for Improved Performance

Analysis of through-chain pricing of food products (Summary version) Freshlogic 24 August 2012

Network Planning & Optimization. Caltex Designs for Growth

Making Strategic Decisions with Oracle Advanced Planning. An Oracle White Paper September 2006

Corpbanca Investor Conference

QAD SOLUTIONS ARE BUILT FOR FOOD AND BEVERAGE MANUFACTURERS, BUILT FOR YOU

Inventory management within a food factory

CAPACITY PLANNING IN A SUGARCANE HARVESTING AND TRANSPORT SYSTEM USING SIMULATION MODELLING. ANDREW HIGGINS 1 and IAN DAVIES 2

WILMAR INTERNATIONAL LIMITED Investor Day Presentation

October 16, UNICA s Comments on Brazilian Sugarcane Ethanol Availability for the LCFS.

GLOBAL AND CHINESE GAS DISCHARGE TUBES INDUSTRY, 2016 MARKET RESEARCH REPORT

New Britain Palm Oil Ltd

Areté Inc. Avail Fact Sheet. Production Scheduling. Syrup Scheduling. Raw Material Scheduling

Strategic planning in LTL logistics increasing the capacity utilization of trucks

Network Optimization using AIMMS in the Analytics & Visualization Era

Why is SAS/OR important? For whom is SAS/OR designed?

Shree Renuka Sugars Limited Brazilian subsidiaries results for Quarter ended 30 th June 2012 Conference Call Transcript October 04 th, 2012

GLOBAL AND CHINESE BUSWAY AND BUS DUCT INDUSTRY, 2016 MARKET RESEARCH REPORT

Supply & Demand Management

Farmer field school networks in Western Kenya

B u n d a B e r g S u g a r B u n d a B e r g S u g a r

Aperitif. Packaging: 750 ml. glass bottles 750 ml Height box: Distribution line: 31,5 cm Length box: 29 cm Depth box: 19,5 cm Net weight box:

Non-exhaustive list of issues and questions to facilitate preparations for bilateral meetings

HP Project and Portfolio Management 9.3 Adoption Readiness Tool (ART)

Delivering a Competitive Edge Across the Supply Chain

GPS BASED TRUCK DISPATCH SYSTEM (TDS) IN HIGHLY MECHANIZED BAUXITE MINES A CASE STUDY.

Inventory basics. 35A00210 Operations Management. Lecture 12 Inventory management. Why do companies use inventories? Think about a Siwa store

Infor Food & Beverage for the beverage manufacturing industry

Tapping the benefits of business analytics and optimization

A sugar distribution network: Designing and planning. Mehdi Sharifyazdi

Introduction to Strategic Supply Chain Network Design Perspectives and Methodologies to Tackle the Most Challenging Supply Chain Network Dilemmas

A Production Planning Problem

The sunliquid process - cellulosic ethanol from agricultural residues. Dr. Markus Rarbach Group Biotechnology Biofuels & Derivatives

Improving Forestry Transport Efficiency through Truck Schedule Optimization: a case study and software tool for the Australian Industry

June 2015 From Nature to Green Energy

Combining GLM and datamining techniques for modelling accident compensation data. Peter Mulquiney

Global Supply Chains in the World Economy

Scope of Supply Chain Management (SCM)

Guidance for Industry

Best Practices for Transportation Management

United Plantations Africa Limited

Steel supply chain transformation challenges Key learnings

MANAGEMENT INFORMATION. Prepared By: Hardeep Singh

FACTORS AFFECTING THE VIABILITY OF SMALL SCALE SUGARCANE BUSINESSES A CASE STUDY OF KDDP BY KENNETH TSABEDZE

Optimize Field Service With Automated Scheduling and Dispatch

Basics of Supply Chain Management (BSCM) Curriculum

Predicting and controlling moisture content to optimize forest biomass logistics

Software for Supply Chain Design and Analysis

DESIGN AND PLANNING OF THE BIOETHANOL SUPPLY CHAIN VIA SIMULATION-BASED OPTIMIZATION: THE CASE OF ARGENTINA

Meeting the Network Optimization Challenge Balancing Service, Contribution and Asset Return for the Global Business Unit

Logistics software implementation in Austrian forest and timber industries

Truck aftersales: Roadmap to excellence. Roland Berger Strategy Consultants GmbH Automotive Competence Center July. 2014

Optimization of Inventory System: A Case Study of Haldiram Bread Industry

Improving Offshore Supply Chain by Predictive Asset Management Making Smarter Business Decisions

Chapter 10: Network Flow Programming

Integrated Business Planning (Advanced S&OP) Course

A MULTI-PERIOD INVESTMENT SELECTION MODEL FOR STRATEGIC RAILWAY CAPACITY PLANNING

SUMMARY NATIVA CORPORACIÓN S.A.

Application of linear programming methods to determine the best location of concrete dispatch plants

Sales & Operations Planning Training - UK Consultant

Index Insurance in India

Category 15: Investments

LOGISTICS SOLUTION FOR NUSTAR ENERGY

Linear Programming. Solving LP Models Using MS Excel, 18

Optimized Scheduling in Real-Time Environments with Column Generation

Hashim Hago Group. Group Structure. Hashim Hago Group consists of ten different companies covering various production and services sectors

Product Documentation SAP Business ByDesign Supply Chain Setup Management

PeopleSoft White Paper Series. Evolving from Distribution Requirements Planning to Collaborative Supply Chain Planning

Transcription:

Planning production and logistics at a major sugar company in Argentina Gustavo Braier, Javier Marenco Braier & Asociados Consultores - www.papyro.com Miguel Casares, Miguel Kremer, Alberto Salvado Ledesma SAAI - www.ledesma.com.ar ALIO/INFORMS Joint International Meeting - Buenos Aires, June 6-9, 2010

Outline Overview of the company and the planning process Development of a linear programming model to assist the planning process Model features Software application Conclusions and current challenges

Overview of the company Ledesma SAAI: Argentine company, leader in the sugar, paper, citric fruits, and citric juice markets. By adding new technologies and investing, Ledesma transformed its original sugar mill and refinery into an agricultural/industrial complex, involving different activities in many Argentine provinces.

Overview of the company Over 6.000 employees. Agricultural/industrial complex: 37,000 hectares planted with sugar cane. Sugar, alcohol, sugar cane cellulose, and paper plants. 600 km of roads built and maintained by the company. 1,400 km of irrigation channels. Other plants throughout the country, and headquarters in Buenos Aires.

Overview of the company Over 50.000 tn. of refined sugar per month during the harvest period, and about 46.000 tn. per month during non-harvest months. Harvesting: From May to November. Production: From May to February/March. The refinery produces a continuous flow of two kinds of sugar, in fixed proportions: 63 % Blanco refinado (premium quality) 37 % Común Tipo A (standard quality)

Overview of the company Range of packaged products from 1 kg. home bags to 1.250 kg. industrial big bags.

Overview of the company The refinery and packaging plants are located in the industrial complex in Jujuy province. 10 depots, four of them devoted to exports + local markets. Two companies provide railroad transportation, starting from Jujuy and Tucumán, respectively. Transportation by truck only allowed along prespecified routes. Most complicated: Jujuy-Bs. As. via Tucumán, by truck, train, and truck, with transshipment costs.

Overview of the company The refinery and packaging plants are located in the industrial complex in Jujuy province. 10 depots, four of them devoted to exports + local markets. Two companies provide railroad transportation, starting from Jujuy and Tucumán, respectively. Transportation by truck only allowed along prespecified routes. Most complicated: Jujuy-Bs. As. via Tucumán, by truck, train, and truck, with transshipment costs.

Overview of the company The refinery and packaging plants are located in the industrial complex in Jujuy province. 10 depots, four of them devoted to exports + local markets. Two companies provide railroad transportation, starting from Jujuy and Tucumán, respectively. Transportation by truck only allowed along prespecified routes. Most complicated: Jujuy-Bs. As. via Tucumán, by truck, train, and truck, with transshipment costs.

Overview of the company The refinery and packaging plants are located in the industrial complex in Jujuy province. 10 depots, four of them devoted to exports + local markets. Two companies provide railroad transportation, starting from Jujuy and Tucumán, respectively. Transportation by truck only allowed along prespecified routes. Most complicated: Jujuy-Bs. As. via Tucumán, by truck, train, and truck, with transshipment costs.

Sugar production and supply chain

Sugar production and supply chain

The planning process The planning process is in charge of the planning team, a 4-person team established in 2001. The planning process is performed in monthly meetings, and is based on the sales forecast.

Outline Overview of the company and the planning process Development of a linear programming model to assist the planning process Model features Software application Conclusions and current challenges

Development of a linear programming model In 2004, Ledesma deployed an initiative to incorporate operations research into the planning process. As a consequence, we developed a linear programming model in order to represent the planning decisions, intended to assist the planning team: Monthly decisions with a 13-month planning horizon. Includes production, packaging, and transportation decisions. Objective: Minimize costs while satisfying demand.

Modelling of production and packaging decisions

The production/logistics interface

Linear programming model The linear programming model from the May, 2010 scenario has: 74.741 variables, 72.476 constraints, 318.067 nonzero elements (density 0.0058 %). The model was coded in a proprietary modelling language, and involves 53 groups of variables and 134 blocks of constraints. Model generation and solution (with Mosek 5 LP solver) in less than 5 minutes.

Computational application We developed a software tool to manage scenarios, solve the model, and analyze the results. Possibility of fixing some model variables and solving for the remaining decisions.

Computational application Set of pre-solving warnings, in order to detect possible infeasibilities and unwanted situations. Set of post-solving solution highlights on the problems and shortcomings of the obtained solution.

Current status The model provides acceptable plans and has been used in parallel with the manual planning since 2008. The model outputs are taken as suggestions for the manually-generated plan. Ultimate goal: Replace the manual planning by the model solution, with manual changes a posteriori and/or variable fixings. We are currently undergoing a tuning process, in order to tackle minor solution shortcomings.

Outline Overview of the company and the planning process Development of a linear programming model to assist the planning process Model features Software application Conclusions and current challenges

Conclusions and current challenges The planning problem for the production, packing, and transportation problems for the sugar business of Ledesma SAAI can be succesfully modeled with linear programming. The solution times are very good. The solution quality is reasonable, although the tuning process is not finished. A fully-automated decision system is not possible, but how far can we reach in assisting the planning team decisions? Automatic strategical suggestions? Online re-planning? Weekly decisions?