In suply chain management and logistics you will encounter a lot of quantitative optimization problems. To solve those optimally, you usually need computing power, and smart algorithms. Stelling Consulting comes from this background.
A. Supply chain network design & quantitative optimization consultancy
Stelling Consulting solves quantitative problems, often supply chain related, using Monte Carlo simulation, simulation, (LP/MIP) optimization, and other Operations Research techniques. Supply chain network design requires experience with data collection/cleansing/validation and network modelling.
B. Supply chain network design web apps (SaaS, in-house)
Stelling Consulting develops its own software, such as the worldwide used Centers‑of‑Gravity Calculator. See also top menu Supply Chain Web Apps.
C. Development of Excel VBA applications
Stelling Consulting has 20 years of experience developing all sorts of advanced Excel VBA applicaties. All manual operations within Excel can be automated, using VBA. Excel offers a sheer amount of functionality that can be used in powerful and user-friendly applications.
This MS Excel VBA application has been developed for a waste company that collects waste in a hundred locations and processes it in several hundreds of locations. Each location has fixed and variable operating costs, minimum and maximum processing capacities and technical restrictions. If required, several types of waste can be mixed to make the flow processable on a certain location.
How should the waste flow, in order to minimise costs, while adhering to all constraints?
To answer this question, this MS Excel VBA application interfaces with mathematical software (AIMMS which uses the CPLEX solver) and a route planner (TLN Planner).
Also the cost effect of having less or more capacity is determined.
This information is useful in negotiations about prices to be paid for hiring capacity.
Text below - about this project done by Alrik Stelling of Stelling Consulting (then Deloitte consultant) and Harry Westerbeek (project manager Strategy & Development of SITA Nederland) - was published as a reference case on the website of AIMMS. That website currently shows recent cases only. Also, an article about this project has been published in the well-known Dutch magazine ITLogistiek.
SITA lowers transport and processing costs of waste management through mathematical optimization
SITA Nederland is a market leader in waste management in the Netherlands, with a turnover € 443 million in 2003. It serves 80,000 companies, and 100 municipalities with a total of 1.8 million inhabitants. SITA Nederland has lowered its transportation and processing costs using a strategic and tactical mathematical optimization tool (MMX II) developed in cooperation with Deloitte using the AIMMS software.
Lowering costs in the waste industry is essential for increasing the current low profits
The waste industry supply chain is shown schematically below:
Waste volumes in the Netherlands are split as follows: household 15%, business/government 9%, industry/agriculture 36%, construction/demolition 34%, others 6%. Waste processing volumes are divided as follows: incineration 11%, landfill 14%, recycling 75%.
Supply and demand play a part, and are regulated by the waste trade. Such a trade exists because some waste companies focus on collection, while others focus on processing.
The average profit margin in the industry was as low as 4% in 1999. Profit margins can change rapidly due to the tax system, legislation, support for recycling, and new process technology: for example, between 1996 and 1999, the margin on 'incineration' dropped from 21% to 1%. Transportation and processing costs account for more than 50% of total costs. Minimizing these costs is thus important in increasing the low profit margins.
Determine processing center use and waste flow
SITA's planning question is which centers to use, and how waste should flow among them, to minimize transportation and processing costs.
Waste is collected and temporarily stored at Transfer Centers; the collection itself is not included in the model. Several types of waste are collected with various characteristics, such as chloride percentage. Waste is generally processed in three steps, each representing a different type of process. Step 1 is carried out in one of the Processing Centers 1, step 2 in a Processing Center 2, and step 3 in one of the Final Processing Centers. Sometimes not all the steps are necessary, and some centers can carry out more than one step. In total, there are more than a hundred possible ways of processing waste arriving at a Transfer Center.
In terms of modeling, each center has its own location, start up costs, and operational costs. Naturally, each center has a fixed processing capacity, but also other technical constraints such as only being capable of processing a waste flow with a chloride percentage within a certain band. In order to match these constraints, several types of waste can be mixed but there are no fixed recipes of waste flows. Transportation costs depend on waste characteristics, transport distance and time, and truck costs per mile and per hour.
All the Transfer Centers are fully-owned by SITA, but SITA does hire additional processing capacity from others. Contractual obligations - non-technical constraints - limit the options in deciding whether or not to outsource a waste processing step.
SITA's planning need is to optimize the usage of the various Centers and the flows of waste such that the transportation and processing costs are minimized while taking into account the situation described above (technical and non-technical constraints).
MMX II answers SITA's planning needs
MMX II provides an answer to SITA's planning question and is used on both tactical (monthly planning) and strategic levels (longer term what-if scenarios). The core of MMX II is a mathematical Mixed Integer Programming model built in AIMMS. AIMMS itself runs as an optimization component in the background, and is connected to a user interface, built in MS Excel using Visual Basic for Applications (VBA).
The MMX II process consists of five steps
Waste parameters and waste quantities collected at all the Transfer Centers
Transport cost parameters
Center parameters: cost parameters, location, technical restrictions (e.g. chloride limits), and non-technical restrictions (e.g. minimum volume to be processed due to contractual obligations)
Data validation / Network generation
Validation of a-priori assignments etc.
Automatic retrieval of journey times and distances between locations. Achieved through a 'separate' VBA interface with the TLN Planner (the standard route planner used by the Dutch transport sector)
The network (600 nodes connected by 30,000 arcs) is then built up automatically (in VBA) in the appropriate format, and then delivered to the standard AIMMS-Excel interface.
Using the mathematical solvers underpinning AIMMS, the following are calculated: waste flows (what amount of what waste from where to where) through the network, shadow prices, transportation costs, and processing costs. The costs are then minimized.
On costs, waste flows, activated centers, etc.
On shadow prices (for example, what would costs have been if more/less processing capacity was available)
On integrated costs, calculated by running through all the steps and assigning costs to each step according to volume or otherwise - and summing all the costs (in VBA)
Validation by planners
Apart from the tactical planning - resulting in a plan minimizing monthly costs - the tool is also used for strategic planning by running different scenarios. The derived shadow prices are useful in the negotiations over long-term prices to be charged by other waste processing companies for hiring their processing capacity.
SITA has reduced annual operational costs by € 400,000
SITA has reduced its yearly operational costs by € 400,000 using MMX II, with project costs as low as € 35,000. The whole project has been the equivalent of two months of work, spread over five months.
Having a complete view of the supply chain, decisions are no longer suboptimal. Nowadays, waste is transported from one plant to another if the decrease in total processing costs exceeds the increase in transportation costs. Previously, waste would rarely cross SITA's regional borders since regional managers did not have an overall view of the full chain.
The cost reductions mainly stem from better utilizing the processing locations. Further, even the total transportation costs have been reduced.
The success of MMX II has been rewarded with an innovation award within SUEZ, the parent company of SITA. In September 2004, an article was published in the well-known Dutch magazine ITlogistiek focusing on SITA's user perspective.
The author, Alrik Stelling - a Deloitte consultant specializing in supply chain management - has been responsible for the tool design, tool programming, and formulating the mathematical model in AIMMS.
Harry Westerbeek - project manager Strategy & Development of SITA Nederland - was mainly responsible for describing the requested functionality of MMX II, describing SITA's supply chain, and testing/validating the model.
This MS Excel VBA application shows the impact on inventories and product availability of different planning methods.
Inputs are minimum batch size per product, production speeds per product, total production hours available, setup times between products, product demands and forecasts.
The user chooses planning options/settings, thus creating scenarios.
Outputs are daily production schedules and inventory levels - per scenario - which can be compared to each other.
This proviodes insight into which planning options give the best results (low inventory costs and high service level).
This MS Excel VBA application routes transport flows through a huge European network of roads, waterways, rail roads, air lanes and terminals, while minimizing costs, kilometres, time, CO2 emissions, or a combination. One can define scenarios (e.g. "what happens with costs and CO2 emissions if we forbid a certain modality") and compare scenario results. This provides insight into the possibilities of a modal shift towards more sustainable transport. The application interfaces with Google Earth for geographical visualization. Underlying database is bought from a third party (and reworked).
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Wachtrijcapaciteit Klantverlies als die te laag is
A social welfare bureau wanted to know how many counters to open at minimum, per hour, to keep queue length acceptable. A simulation model - like this demo developed by Stelling Consulting - can help to answer such a question. You can adjust its parameters, and see what happens.
Stelling Consulting has been established in 2008
20 years of expercience in developing Excel applications - as operational software or as tool for optimization studies
For Ikea, Heineken, Coca Cola Enterprises, Disney, Feadship, Reckitt Benckiser, AT Kearney, Medtronic, AON, SITA, Worldbank, Deloitte Consulting, Swissport, Hamburg Süd, Genzyme, De Nederlandsche bank, Postbank, Flora Holland, Centrum voor Werk en Inkomen, Centraal Orgaan opvang asielzoekers, Ministerie van Verkeer & Waterstaat, Connekt, SenterNovem, Hogeschool van Arnhem en Nijmegen, Vintura, Visser & Smit Marine Contracting, UCB, VolkerRail, HDM Pipelines, Acquaint, World of Delights, OIM Orthopedie, Buck Consultants International, Register Belastingadviseurs, Jumbo Spellen, De Rijke Logistics, Valspar, de Alliantie.
15 years of experience with supply chain network design
For Coca Cola EAG, Siemens, DHL, Smiths Medical, Ingenico, Sara Lee, PKN Orlen, MCB, Stryker, Componenta, Henkel, TMD, Cummins, Takeda, Husqvarna, AbbVie, Henry Schein, Carefusion/Becton Dickinson, Hilti, Medtronic, Axalta.
Alrik Stelling (owner) "As a logistician (university degree in business engineering & supply chain management), software programmer, and visual artist (fine arts degree) I combine creativity with '0/1-thinking'. Before founding Stelling Consulting I have worked eight years at Deloitte Consulting as supply chain management consultant/manager, specialized in developing optimization software and strategic supply chain network design. I enjoy creating. If a new application enables the customer to work more pleasantly/faster/flawlessly, or offers the appropriate support for quantitative decision making, then this happy customer becomes a loyal customer!"
Njin-Tsoe Chen (associate) "As a supply chain professional, with a Master in Science, I combine insight and experience in supply chain processes and knowledge of Excel and IT systems. I have extensive experience with the different steps within a supply chain: transport optimization (RFQs), Warehouse design, Business Case calculations, Warehouse management system implementation, supply chain network design, and S&OP. My passion is to improve supply chains. Have processes and people operate at a higher level. I am motived by creating results!"
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