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Exploitable results
Industrial processes are complex. Modelling them can be even more so. Yet this is what the MAPP project partners managed to do. They developed integrated software to help reduce the environmental impacts of industrial processing while lowering production costs and improving product quality. Their software includes all steps from data mining, data capture, database and environmental modelling, to real-time implementation.
The multivariate real-time system was evaluated using three case studies - wastewater treatment at a municipal sewage treatment plant, metal fuel tank production and the phosphating process during truck cabin fabrication. MAPP (multivariate approach for statistical process control and cleaner production) project coordinator, Jonas Rottorp, from the IVL Swedish Environmental Research Institute Ltd explains that MAPP software bridges the gap between process modelling and monitoring.
"There has always been a gap between researchers and the end-users in online process control, particularly using multivariate, real-time systems," he says. "We showed that it is possible to use advanced modelling techniques for process monitoring. Typically this has failed because implementation in the industrial processing environment is too difficult."
By using models describing the relationship between process input and product performance - including economic performance, quality and environmental impact - better process control can be achieved. This results in both cost savings and reduced environmental impacts. The three case studies showed that by using MAPP software, online predictions replaced time-consuming and expensive laboratory analyses. At the same time, operators gained a deeper knowledge of the process and were able to exert tighter process control.
All round better wastewater treatment
Municipal wastewater treatment is essential to control the environmental impacts of human behaviour. It reduces the emissions of organic matter and nutrients. The difficulty with wastewater treatment is to continuously produce clean effluent because the composition and the flow of the influent constantly changes. In addition, the consumption of precipitation chemicals and energy must be considered as their use also has a negative impact on the environment.
The new multivariate modelling techniques, used in combination with dynamic database modelling, solved the difficulties inherent in this very dynamic process, which requires high quality monitoring and control systems. MAPP real-time predictions of the effluent quality and process status was accomplished by using a software sensor for predicting phosphorous in the composition of incoming water.
Rottorp says this is a "real scientific breakthrough" that resulted in savings in precipitation chemicals and energy supply as well as improving the quality of the effluent. MAPP resulted in several significant achievements at the Borlaenge Wastewater Treatment Plant, including the development of an object-oriented database to improve the ability to model the process and the creation of a sophisticated lifecycle inventory of precipitation chemicals that enables online monitoring of environmental impacts.
More efficient fuel tank production
Metal fuel tanks are more resistant during car crashes and safer because they reduce the likelihood of fire. However, their production is more difficult because metal is less malleable and more expensive than plastic.
The MAPP model for the welding of fuel tanks demonstrates the risk of leakage by using the concept of a complex form of analysis. If the analysis yields a value greater than -1, the tank will not leak. Welding experts at Fiat's ILAS factory near Turin, where most tanks are made, pointed out that the junction along the perimeter of the tank is the most critical. This information was factored into the process model.
Application of the MAPP model resulted in fewer actual tests, as there is no need to test tanks in which the model gives a value greater than the threshold. The MAPP model is statistically significant and the results quite easy to interpret. As a result, fewer leak tests are needed due to the initial screening model of the welding result.
Tighter control of painting processes
The phosphating process is an essential metal surface treatment. The phosphating layer serves both as a corrosion protection and as a pre-treatment process for painting. The quality of the layer is critical to the final finishing of the metal product. Because it is an energy and chemical demanding process, optimisation leads to economical and environmental savings.
Knowledge about which process changes are needed to achieve a better product with less impact on the environment can be obtained using MAPP's multivariate model based monitoring and control system.
Operators could follow cost and environmental impact per produced unit in real-time and monitor all process movements. MAPP's monitoring system also revealed the predicted contribution of greenhouse gases, eutrophication potential and cost per produced truck cabin. Quality parameters were measured in real-time using multivariate models.
Using MAPP software at Volvo Truck Corporation resulted in significant cost savings and reduced environmental impacts. Says Rottorp: "Volvo was evaluating the wear and tear caused by weather to the paint used on their trucks every second week. MAPP models enabled the company to do this evaluation three times a day. This resulted in cost savings, improved quality and a reduced environmental impact. Using process control, trucks can be produced using less paint and chemicals. It's a win-win situation."
MAPPing the future
The prototypes developed and the successful demonstration projects at full scale industrial plants clearly shows that problems in using multivariate process models to control various processes have been solved. Future plans including developing the prototype into a new generation of software for process monitoring and control.
"We were monitoring the process but we plan to put more research into how we can better control the process," explains Rottorp. "We will be merging scientific disciplines to enable real-time process control and decision making. This should take about two to three years."
The MAPP consortium included IVL, the University of Warwick, Centro Ricerche Fiat, the Volvo Truck Corporation, Borlaenge Energy, Kenwater (Kemira Chemicals), BioBalance, DELTA, Sigma iSoft and Umetrics.
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