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Preventing Concrete Failures by Reverse Engineering

25 June 2013 | UKZN | Presented by: Steve Schulte – Construction Management Systems

The presenter, Steve Schulte's passion for building quality systems for construction projects, emanating from risk assessments that reveal concrete to be one of the highest risk items for a project, was evident. Common specifying methods, acceptance criteria for concrete, and relevance of various standard test methods were debated, in relation to the cause and effect analysis of concrete failures which point more heavily towards the human factor rather than technology.

Steve then introduced the concept of a reverse engineering process including the installation, calibration and commissioning of a data logger at a batch plant, followed by the reliable, accurate and consistent collection of data from batch plant load cells and other input signals as required. Samples of collected data were presented and the reverse engineering process explained, involving the safe and reliable long term storage of all collected data and the manipulation of collected data for the purpose of pattern recognition, and the calculations required to recompile mix ingredients from data collected by the logger.

Further development on the process will be the engineering of a mathematical algorithm to automatically interpret the nature of all collected data to include pattern recognition techniques, to demonstrate the effects of wind loading, impact loading on load cells, material theft, and calibration and batching activity amongst others. This process will also include reverse engineering calculations comparing the reverse engineered load to specifications and acceptance criteria, to automatically determine whether or not a load of concrete will meet requirements. Loads that do not meet requirements would trigger the management software to send appropriate error messages and instant notification to relevant people before the truck leaves the batch plant in an attempt to proactively avert potential defective product.

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