Customer profile:
Metropolitan Sewer District

Note: These customers were using a previous version of CHARTrunner which has since been integrated into our current SQCpack solution.

Waste treatment facility adopts new approach

While “finger-to-the-wind” calculations may be useful to a sailor deciding which way to tack, such approximations have long ago given way in most industries to decision-making based on data. For Greater Cincinnati’s Metropolitan Sewer District, analyzing data has replaced operators’ guesses and created a more efficient and predictable treatment system.

Treatment supervisor Ken Wegenhart collects and analyzes a variety of data for the organization’s largest facility, the Mill Creek treatment plant. This data includes everything from sludge volume index and mean cell residence time to ratios of mixed liquor suspended solids and return activated sludge suspended solids in the secondary process. The secondary process is biological process and is the “workhorse” of wastewater treatment. “We are essentially bacteria farmers,” Wegenhart explains of the system, noting that the balance between biomass and incoming sewage is essential to the breakdown of pollutants and the reclamation of clean water.

SPC charts reduce tampering and result in a more predictable process

At one time, operators would adjust the system arbitrarily, Wegenhart says. “If it was Friday, they’d decide they needed to change the system for the weekend, regardless of the circumstances.” Statistical process control, using charts to demonstrate changes in the system, has reduced this kind of tampering and resulted in a much more predictable process, he says. But it has not been easy to instill a “data mentality,” when seasoned operators were accustomed to making decisions based on their own experience. In treatment management, Wegenhart says, processes can change frequently, subject to temperature, rainfall, and demand. Since it can take more than four days for a volume of biomass to go through the treatment process, it is tempting for operators to tamper, rather than evaluate data. But this is changing at MSD.

Run charts are what Wegenhart uses most, primarily because of their usefulness in visually pointing out tendencies or trends. Because of frequent changes in the process, caused by rainfall or other variables, control limits must be recalculated often. He says that these recalculations suggest to some that control limits are arbitrary, so he resorts to run charts to simplify the visual impact on understanding.

Data collected with Excel is charted with CHARTrunner

The MSD staff participated in PQ Systems’ quality management training in the early 90s, with ongoing team training by internal facilitators. The staff is now engaged in a reliability maintenance program through the University of Dayton. The key, Wegenhart says, is “making decisions based on data” and thereby assuring improvement in the system. Currently, he collects data with Excel, and then charts it with CHARTrunner from PQ Systems, Inc. The charts help operators predict changes with a higher level of certainty, giving them a greater sense of control over the system and confidence in the changes that they make.

And when that happens, the organization and its customers are the ones who benefit most, since controlling the system helps to control costs and improve quality. No one gains, on the other hand, from the old “finger-in-the-wind” approach.

Except maybe sailors.