Improving Hot Mix Asphalt Production Using Computer Simulation and Real Time Optimization Min Zhang 1 ; Michael Heitzman 2 ; and Alice E. Smith 3 Abstract: The quality of hot mix asphalt is affected by the quality and consistency of input aggregates and the control of the production process. To improve the quality of hot mix asphalt, both the aggregates gradation and the process variables must be considered. Current practice involves taking samples from actual production and analyzing them in the lab. The entire process can take two hours, which, along with being expensive, is not amenable to real time online process control or even in knowing how much product is actually out of speci- fication. In this paper, an online control system is proposed that can be used to significantly decrease the analysis time and adjust production by using discrete time stochastic simulation combined with algorithmic optimization. Additionally, the system can readily show when a mix is out of specification without lag time or physical experimentation. Results show that this approach can effectively control the production process resulting in improved quality. This is the first known such application in hot mix asphalt online process control. DOI: 10.1061/ (ASCE)CP.1943-5487.0000302. © 2014 American Society of Civil Engineers. Author keywords: Hot mix asphalt; Quality control; Simulation; Real time optimization; Aggregate gradation. Introduction Hot mix asphalt (HMA) has a very important part in highway construction and its quality is key to longevity and durability of pavement. Over the past two decades, attention has been given to improving the laboratory tests used for quality control of HMA by making them faster and less variable. Although this has been beneficial, testing is still quite time-consuming and expen- sive. Online real time control of the HMA process is a goal that has not yet been realized fully (West 2005). The quality of HMA is affected by the quality of the input ag- gregate and the production process, and the control of the HMA production process is of fundamental importance in assuring aggre- gate compliance. However, previous studies (Hall and Williams 2002; Turochy et al. 2006; Turochy and Parker 2007) reported that state agencies’ verification testing and the contractor quality control testing can show significant variation with respect to the material analysis. A study developed by the California Department of Trans- portation (Douglas et al. 1999) analyzed the case when material from more than one plant was delivered to the same jobsite. They recommended some special procedures be implemented when this occurs such as not intermingling different plant material at delivery, making sure sampling is not done with comingled material, and making separate control charts for each plant. However, in practice, ensuring uniformity of raw material is problematic, at best. The goal of production process control is to improve the ability of the hot mix plant to produce material that is consistent and near target. This goal goes well beyond simply staying within specification compliance. Because of the time required for current sampling and testing methods (for example, currently four 50 pound samples represent 1,000–3,000 tons of pro- duction per day), it is difficult, at best, to speculate on the actual amount of production variation. Each quality control sample typ- ically only represents 0.005% of the production or stated another way, each sample represents 20,000 units of production. Because of these widespread quality issues, researchers have proposed methods to implement quality control for HMA. Guo uses an uncertainty analytic hierarchy process method to improve the quality of HMA (Guo et al. 2009); it is based on a large amount of data collected from actual asphalt production and laboratory test- ing results. Tsai and Monismith (2009) describe a methodology to determine a sampling scheme and selection of sample size for qual- ity control of HMA. Gopalakrishnan et al. (2008) uses computer simulations to study the compaction process in HMA. White et al. (2002) establish an online database to monitor hot mix asphalt proj- ects throughout their life cycles and bring computing technology and HMA construction together to create real time construction tools. Kabadurmus et al. (2010) presents a basic simulation meth- odology to establish an online process control of HMA. Kabadur- mus’ s effort provided the earlier version of the optimization algorithm used within this paper. Other than this last paper, the quality control efforts cited above did not approach an online (real time) system addressing production quality. Instead they are offline methods based on data repositories. This still leaves the consider- able problems of both time lag in detecting out-of-specification mix and expensive and intermittent physical testing of mix. The purpose of this paper is to develop a more robust online control model that can be used for aggregate gradation control to improve the quality of the HMA production process and repre- sents the first known such effort. This paper considers varying in- fluence elements, including gradation variation in the cold-feed bins, the job mix formula (JMF) tolerance set by the customer, and several control policies. The HMA online control system ad- justs the proportion from each bin of aggregate to optimize quality once it detects that the process is departing from a controlled state. The hardware and data-processing software to obtain real time (that is, continuous) measurements is a major component for a complete 1 School of Mechanical Engineering, Southwest Jiaotong Univ., Chengdu 610031, China. 2 National Center for Asphalt Technology, Auburn Univ., Auburn, AL 36830. 3 Dept. of Industrial and System Engineering, Auburn Univ., Auburn, AL 36849 (corresponding author). E-mail: smithae@auburn.edu Note. This manuscript was submitted on July 24, 2012; approved on March 5, 2013; published online on March 7, 2013. Discussion period open until July 24, 2014; separate discussions must be submitted for individual papers. This paper is part of the Journal of Computing in Civil Engineer- ing, © ASCE, ISSN 0887-3801/04014011(8)/$25.00. © ASCE 04014011-1 J. Comput. Civ. Eng. J. Comput. Civ. Eng. 2014.28. 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