Online Monitoring Optimizes Polymerization Processes

Plant enhances product quality and reduces cycle times

By Grant Heard and Scott Meikle, Nalco Water, and Alex W. Reed and Michael F. Drenski, Fluence Analytics

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While makers of commodity polymers generally rely on high-throughput continuous processes, many specialty polymer manufacturers use batch processes. This meets customer requirements for flexibility in making a wide range of products on time without changes to the plant infrastructure. In addition, specialty polymer manufacturers regularly develop product recipes featuring new properties; these are often produced using industrial equipment in a relatively short period of time.

Nalco Water, an Ecolab company, is a world leader in high-value polyacrylamide (PAM) polymers and other products and services for industrial and municipal water treatment as well as other applications. Many of these products are made at Nalco’s facility in Garyville, La. In some applications of PAM, such as in cosmetics or contact lenses, human contact with the product may occur, necessitating very tight control of residual monomer specifications.

A common issue when producing polymers using batch processes is knowing the exact endpoint at which to stop the reaction and begin the next run. Specialty polymers like PAM must adhere to rigorous quality specifications, which include safety-related parameters like residual monomer (restricted to ppm levels) and in-use properties like viscosity. Without a way to directly monitor what’s happening in the reactor, checking of these specification parameters must take place in the quality control lab after the reaction is over. To avoid off-spec batches, many plants usually adopt a conservative approach — running the reaction much longer than necessary, consuming energy, operator time and equipment availability. Clearly, a more-dynamic approach to monitoring each batch is desirable due to changes in day-to-day conditions from a number of variables including feedstocks, personnel, temperatures and equipment performance.

So, what if a person could “see into the reactor” and track key parameters as the reaction occurs? That’s exactly what ACOMP (which stands for Automatic Continuous Online Monitoring of Polymerization reactions), a smart manufacturing system produced by Fluence Analytics, does.

ACOMP is an integrated hardware/software analytical tool that continuously takes a very small sample of liquid from the reactor and analyzes it using advanced characterization techniques (Figure 1). Ultraviolet absorption or differential refractometry characterization determine the continuous polymer concentration. This concentration enables characterizing the weight average molecular weight and reduced viscosity of the polymer in real time throughout the entire polymerization process.

ACOMP, which is tied into the distributed control system for increased plant connectivity, generates automated reports detailing initial reactor conditions, rate of conversions, conversion levels, time to target conversion, and product quality values for each polymerization (Figure 2). These reports are stored in a database, allowing for quick historical reference; they identify ways to improve efficiency and reduce variance not only of product quality but also of reaction process time from batch to batch. This enables operators to tighten up standard operating procedures (SOPs), ensuring that each polymerization follows “golden batch” kinetics.

Adoption At Plant

In 2013, Fluence Analytics began a dialog with Nalco to discover its needs and determine how ACOMP could meet them. Following some initial research in cooperation with Nalco’s plant and R&D professionals, the two companies decided to pursue a joint technology development project. The result was the first-ever industrial ACOMP system installation — on one of Nalco’s inverse emulsion PAM reactors in Garyville in October 2014. Nalco’s engineering team worked with Fluence Analytics to design and install a fast loop for an ACOMP sampling point, specify required utilities and tie-ins into the process and control system, and develop SOPs for startup and training. All startup procedures and personnel training were executed post system startup with operators utilizing the ACOMP system through the plant control system to successfully monitor reactions.

During this time, global capacity for PAM was very tight due to the U.S. fracking boom. (PAM is used to enhance oil recovery in hydraulic fracturing.) Nalco’s visionary support and willingness to explore new smart manufacturing technologies by partnering with a startup paid dividends. Because ACOMP allowed Nalco to “see inside its reactor,” the company was able to reduce its production batch cycle times for a wide range of its products. After startup, reactions were monitored to understand the endpoint of the batches (Figure 3). Following the monitoring of more than 100 reactions, it was calculated that ACOMP enabled a 15–20% reduction, on average, in batch cycle times across Nalco’s PAM products manufactured in one reactor. ACOMP was able to expand monitoring to almost all products made in the reactor. After significant parallel use, operating and utilizing ACOMP data for cycle time optimization eventually became a plant SOP.

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