40 | Sector Focus: Software
◄ plans, it has faced challenges in its implementation. It cannot deal with real-world complexity or respond rapidly to change. New technology based on artificial intelligence (AI) overcomes these problems and has the potential to revolutionise the planning and operation of the forest product supply chain.
FROM UNIVERSITY RESEARCH TO GLOBAL SUCCESS
The Opturion story started at Imperial College London, where Professor Mark Wallace (now research director at Opturion) led a team of researchers to develop a new form of optimisation, constraint programming, part of the AI optimisation branch.
One very successful project was with CISCO for internet traffic optimisation. It was so successful that CISCO adopted the technology in 2004. At the same time, Prof Wallace moved to Monash University in Australia to continue his research. A further seven years of work paved the way to form Opturion, a university spin-out facilitated by the Commonwealth Scientific and Industrial Research Organisation. Ten years later, Opturion has many large customers in Australia and operations in the UK and Chile. The company has successfully applied its technology in supply chains (manufacturing, transport and logistics) and, more recently, new energy.
HOW AI IS OPTIMISING SUPPLY CHAINS Unlike traditional approaches such as mixed-integer linear programming (MILP), constraint programming does not need to approximate or simplify the business rules
and relationships that define the problem. Instead, it takes a very pragmatic approach and seeks legal and valid solutions (called feasible solutions). Once it finds a feasible solution, the algorithm proceeds to find better and better solutions. After a predetermined time or other criterion, the process finishes. Consistency of time is a crucial advantage as the solution time of MILP is unreliable, if it solves at all. Another quality is the ability to quickly produce a feasible solution, essentially to re-optimise when things change. Finally, the technology is scalable to address large problems in a reasonable time. By their nature, supply chains are complex, large and dynamic, meaning that AI-based optimisation will naturally become the technology of choice.
HOW OPTIMISATION WORKS ACROSS OTHER INDUSTRIES
Supply chain optimisation is a well- established technology in industries such as bulk chemicals, petrochemicals, mass production and food and beverages. The predominant application is tactical planning, typically aggregating into daily or weekly ‘buckets’ where the traditional approaches work best. Opturion has taken this to the next level in two aspects:
• We are providing solutions with detailed schedules. As well as day-by-day, the
optimiser can produce hour-by-hour or even minute-by-minute solutions. This ability offers opportunities for better equipment co-ordination and consideration of driver breaks, for example.
• We use the same technology to provide
long-term, medium-term, and operational optimisation within the same environment, reducing development and maintenance costs and delivering consistent results.
This new capability has enabled new solutions in more complex or dynamic areas:
• Sectors with highly variable and dynamic supply chains include advanced
manufacturing, make-to-order, specialty retail and last-mile logistics.
• Complex supply chains, like fuels and bulk liquids, have challenges with just-in-time,
scheduling and routing, and individual vehicle load planning considerations.
THE UNIQUE CHALLENGES OF FORESTRY OPERATIONS
Forestry operations are complex and require the co-ordination of harvesting, loading and transporting equipment to deliver different species of wood to customers such as sawmills, pulp mills and plywood production plants. Like retail, there are elements of push (production rate anticipating future demand) and pull (the customer has placed an order). Similarly, there are ‘sell-by’ dates depending on the product: harvested wood starts to dry out and split, making it unsuitable for plywood and sawmills, but this does not apply to wood for pulping. Additional challenges exist around:
• Variability in the size and weight of the wood
• Harvesting and loading rates, both of which are subject to weather conditions,
the terrain, the amount of daylight and the dimensions of the wood
8 loads Supply of product P1: 10 loads Supply of product P2: 3 loads SOURCE A Supply of product P3: 5 loads 2 loads Max
Banned supply
5 loads Demand for product P1: 5 loads Supply of product P2: 2 loads SOURCE B 20 loads Supply of product P3: 25 loads Above: Supply and demand planning TTJ | July/August 2024 |
www.ttjonline.com Max Demand for product P3: 20 loads PLANT B Max 3 loads Demand for product P2: 10 loads Max PLANT A Demand for product P1: 8 loads
Max
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