Skip to content

Case Studies

We have supplied our expertise to a range of clients in different industries.

A better feel for the value we can provide can be obtained by a quick look at the case studies below.

  • Dunlop Foams Group: Material Optimisation

    The Problem

    The cutting of polyurethane foam products, such as pillows and cushions, requires large foam blocks to be cut into smaller component sized pieces.

    Dunlop Foams receives orders daily requiring numbers of foam blocks to be cut into many potentially different sized items according to these customer orders. The problem they face is that there are many ways to cut large foam blocks into the smaller pieces needed, but the amount of wasted material depends on the order in which the blocks are cut to size.

    The Solution

    Adelaide Operations Research undertook research into various algorithms that could be applied to the optimal foam cutting problem. Using historical data, and keeping track of off-cuts from each order fulfilled, we determined that the wasted material over a three month period could be reduced by approximately one-third - a saving of potentially $800,000 per year in raw materials.

    Adelaide Operations Research subsequently developed software to

    • Implement the selected foam cutting algorithm,
    • Track leftover materials from the fulfillment of each order,
    • Provide instructions to foam cutters on which off-cuts to use and what series of cuts to use to to fulfill an order.

    The software is in the final development stages and will be field trialled in the second half of 2004.

  • Automotive Manufacture: Ensuring Maximum Capacity

    The Problem

    Major automobile manufacturers often produce a wide range of vehicles on a single assembly line. The time taken to fit various options depends on their complexity and the type of car. There are rules concerning how closely two cars requiring certain options may be spaced on the assembly line. As a result, determining the number of cars that can be built on any given day, given the types of cars that have been ordered, can be difficult to determine.

    If assembly line resources are not used efficiently the maximum capacity may not be achieved, with subsequent impact on the potential revenue that can be generated. It is crucial to know when capacity limitations may occur so that actions can be taken to address the situation.

    The Solution

    We developed software that analyses the end-to-end manufacturing process of one of the plants of a major automobile manufacturer. The software uses vehicle orders, assembly line rules and production information to determine when artificial limitations in capacity might occur.

    When capacity issues are identified, the software can automatically determine which rules are causing the pressure on capacity. Knowing this, production managers can then take action to loosen certain rules, for example by using extra staff at key assembly line stations, in order to increase overall capacity and thus ensure the most efficient operation of the plant overall.

  • Efficient Asphalt Production & Storage

    The Problem

    A major asphalt producer needed to consider the cost benefits in investing in "hot-bins" at their asphalt production plants. Hot bins are used as a temporary storage facility for pre-made asphalt and allow for the stock-piling of asphalt in advance of need, but only on a day to day basis. Each hot-bin can hold one type of asphalt mix and costs of the order of hundreds of thousands of dollars.

    The questions then arise as to :

    • How many hotbins are needed to meet potential manufacturing requirements?
    • What asphalt mixes should be placed in the bins?
    • What are the potential cost savings, if any, achieved through use of hot bins?

    The Solution

    We developed software to analyse historical data on asphalt orders. From this information, profiles of asphalt usage by type and day of week were developed.

    Separately, simulation software of an asphalt production plant was developed and algorithms governing the use of hot-bins defined. The daily asphalt profiles were then run through the simulation in order to determine the waiting times for trucks purchasing asphalt, and hence allowing quantification of the efficiency benefits of using hot bins as compared with current operating procedures.

    The results were subsequently used as an important input to the business case for purchasing hot bin capacity in their South Australian plants.

Teletraffic Research Centre
Address

Level 5, Ingkarni Wardli
The University of Adelaide
SA 5005 Australia

T: +61 8 8313 5413
F: +61 8 8313 4395
Email