Supply Chain Modeling for a Process Industry

2017 ◽  
Vol 8 (2) ◽  
pp. 36-55 ◽  
Author(s):  
Nils-Hassan Quttineh ◽  
Helene Lidestam ◽  
Mårten Ahlstedt ◽  
Sven Olsson
Keyword(s):  
Mathematical Model ◽  
Supply Chain ◽  
Decision Support ◽  
Programming Model ◽  
Decision Support Tool ◽  
Process Industry ◽  
Mixed Integer ◽  
Budget Process ◽  
Process Industries ◽  
Support Tool

Process industries of today differ from other industries in many aspects. The purpose of this paper is to consider these special properties of process industries when developing a mathematical model that can be used as a decision support tool for the supply chain planning for a chemical process industry in Sweden. A mixed-integer linear programming model is developed, and solutions to the model present how the products will be transported between the different sites of the company, the levels of the inventories, the setups and purchases from the external suppliers and also the production rates. The mathematical model takes many special properties regarding process industries into account. By using the results from the model and test different scenarios, the model can be used as an important support tool when making decisions. The decision support tool can for example be used in the company's budget process and thereby improve the chances of future profits increases.

Transparency Issues Within a Transport Buyer and Provider Relationship

2020 ◽  
pp. 78-95
Author(s):  
Eirill Bø
Keyword(s):  
Supply Chain ◽  
Decision Support ◽  
Decision Support Tool ◽  
Food Distribution ◽  
Household Waste ◽  
Support Tool ◽  
Time Parameters ◽  
The Right ◽  
The Cost ◽  
The Relationship

Transport is an important function in the supply chain. This chapter focuses on how to buy a transport service, how to form a transport contract, and how a transparent relationship will influence the risk and the relationship between transport provider and buyer. By developing a decision support tool (DST-model) and calculating the cost and the time parameters, the right price and the cost drivers will appear. The cases described in this chapter are a large Norwegian wholesaler for food, distribution to the retailer, and two Norwegian municipalities collecting household waste. In these cases, the buyer and the provider are acting blind in setting the transport price. This means that there is a huge risk for either a bankruptcy by the transport provider or an overpriced transport for the buyer.

scholarly journals Model-Based Decision Support Tools at Jugos S.A. Concentrated Fruit Juice Plant

2020 ◽  
Vol 50 (4) ◽  
pp. 255-268
Author(s):  
Aníbal M. Blanco ◽  
M. Susana Moreno ◽  
Carolina Taraborelli ◽  
Flavio D’Angelo ◽  
Facundo Iturmendi ◽  
...  
Keyword(s):  
Decision Support ◽  
User Interfaces ◽  
Decision Support Tool ◽  
Raw Material ◽  
Mixed Integer ◽  
Support Tool ◽  
Support Tools ◽  
Optimal Target ◽  
And Storage

We describe the development of a decision-support tool to assist in the operations of a large concentrated apple and pear juice plant. The tool’s objective is to generate detailed schedules of clarified juice batches to be produced in the following weeks considering incoming fruit forecasts, commercial commitments, and infrastructural constraints. The tool is based on two interactive modules, PLANNER and SIMOPT, with different and complementary purposes. Each module is based on mixed-integer models with specific inputs, outputs, and user interfaces. PLANNER consists of three submodules: (i) planning assigns a batch of concentrated juice to be produced on a specific day, taking into account cleaning activities, rest days, raw material availability, and production and storage constraints; (ii) preprocessing organizes juice orders in batches; and (iii) pooling provides a detailed monitoring of semielaborated juice in storage pools in terms of inventories and sugar and acid content. Finally, SIMOPT provides a detailed optimal operative condition of the plant together with a thorough calculation of specific costs. This information is used by PLANNER to evaluate the corresponding economic objective functions. Besides providing optimal target conditions to the plant and feasible production schedules, the developed tools generate production guidelines in the long term and allow performing scenario studies.

scholarly journals An innovative decision support tool for liquefied natural gas supply chain planning

2020 ◽  
Vol 5 (1) ◽  
pp. 121-136
Author(s):  
Christos Papaleonidas ◽  
Dimitrios V. Lyridis ◽  
Alexios Papakostas ◽  
Dimitris Antonis Konstantinidis
Keyword(s):  
Supply Chain ◽  
Decision Support ◽  
Natural Gas ◽  
Decision Support Tool ◽  
Liquefied Natural Gas ◽  
Maritime Transportation ◽  
Management Tool ◽  
Content Type ◽  
Support Tool ◽  
Tramp Shipping

Purpose The purpose of this paper is to improve the tactical planning of the stakeholders of the midstream liquefied natural gas (LNG) supply chain, using an optimisation approach. The results can contribute to enhance the proactivity on significant investment decisions. Design/methodology/approach A decision support tool (DST) is proposed to minimise the operational cost of a fleet of vessels. Mixed integer linear programming (MILP) used to perform contract assignment combined with a genetic algorithm solution are the foundations of the DST. The aforementioned methods present a formulation of the maritime transportation problem from the scope of tramp shipping companies. Findings The validation of the DST through a realistic case study illustrates its potential in generating quantitative data about the cost of the midstream LNG supply chain and the annual operations schedule for a fleet of LNG vessels. Research limitations/implications The LNG transportation scenarios included assumptions, which were required for resource reasons, such as omission of stochasticity. Notwithstanding the assumptions made, it is to the authors’ belief that the paper meets its objectives as described above. Practical implications Potential practitioners may exploit the results to make informed decisions on the operation of LNG vessels, charter rate quotes and/or redeployment of existing fleet. Originality/value The research has a novel approach as it combines the creation of practical management tool, with a comprehensive mathematical modelling, for the midstream LNG supply chain. Quantifying future fleet costs is an alternative approach, which may improve the planning procedure of a tramp shipping company.

Distributed Supply Chain Simulation as a Decision Support Tool for the Semiconductor Industry

SIMULATION ◽  
2003 ◽  
Vol 79 (3) ◽  
pp. 126-138 ◽  
Author(s):  
Peter Lendermann ◽  
Nirupam Julka ◽  
Boon Ping Gan ◽  
Dan Chen ◽  
Leon F. McGinnis ◽  
...  
Keyword(s):  
Supply Chain ◽  
Decision Support ◽  
Semiconductor Industry ◽  
Decision Support Tool ◽  
Support Tool ◽  
Supply Chain Simulation

An approach and decision support tool for forming Industry 4.0 supply chain collaborations

2021 ◽  
Vol 125 ◽  
pp. 103391
Author(s):  
Sonia Cisneros-Cabrera ◽  
Grigory Pishchulov ◽  
Pedro Sampaio ◽  
Nikolay Mehandjiev ◽  
Zixu Liu ◽  
...  
Keyword(s):  
Supply Chain ◽  
Decision Support ◽  
Industry 4.0 ◽  
Decision Support Tool ◽  
Support Tool
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