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This article was published in the April issue of International Cement Review in 2015.

Transport optimisation software can be a win-win for all

Transport optimization software can cut cement distribution costs significantly. That's great for all cement producers who run their own fleet of trucks. But what if you subcontracted deliveries to hired hauliers and franchisees? Who will benefit from the investment in IT infrastructure? With the right set-up it can be a win-win outcome for both parties.

by Thomas Bergmans, Julien Drevon and Dirk Schlemper, INFORM GmbH, Germany

Cement transport plans usually have a limited shelf life. Affected by daily challenges such as last-minute orders, cancelled or delayed jobs, long waiting queues, or truck or machine breakdowns, they quickly become obsolete. Schedulers and dispatchers are forced to review and adjust their planning decisions constantly – right up to the moment before execution. Available conventional planning software may offer some relief: they automatically copy order data from the ERP system, provide user-friendly graphical interfaces to help assigning loads to trucks, calculate schedules and trip times, visualise routes on maps. GPS telematics components can also track truck position and delivery status in real time. But with a large truck fleet on the road, numerous cement plants and delivery sites spread across a wider region, huge data volumes have to be handled to find a set of good routes. The human brain is not up to this sort of challenge. Even experienced schedulers and dispatchers are stretched to their limits, assuming they only work with software that does not have its own intelligence.

Intelligent optimization

A giant leap forward in planning technology is the use of intelligent optimisation software packages. They are equipped with algorithms that analyse a virtually endless number of scheduling decisions in real time and identify those that are ideal for minimising costs and maximising service quality – based on the business criteria defined. Figure 1 compares real-world data from a producer in the construction industry in Europe – before and after optimisation. The scenario reflects a typical working day and is based on the following parameters: five plants, two depots and 103 bulk orders for 78 different customer delivery locations.

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