Abstract
The water industry has been facing a lack of young, qualified workers for many years while simultaneously having aging employees retire or change fields. This is creating a lack of workers in treatment plants. As technology has become more advanced, the industry has also become more automated. This should make it easier in the future to attract and train young people to the sector due to their interest in automation and computer learning. The creation and adaption of didactic computer simulators and virtual reality programs is one method the water industry has begun using in training to try to attract young workers. We use Festo’s Environmental Discovery System® (EDS) for Water Management to prove the usefulness of these systems.
Highlights
Water and wastewater treatment plants are facing the crisis of an aging workforce
Some areas of the water sector have skilled workers that are significantly older than the national average, such as water treatment plant operators, who have an average age of 46.4 years
This paper looks at an iron flocculation experiment done using Festo’s Environmental Discovery System® (EDS)® Water Management System as a model experiment, where synthetic raw water was created by adding sodium hydroxide to tap water and ferric chloride was used as a coagulant
Summary
Water and wastewater treatment plants are facing the crisis of an aging workforce. According to a report by the Brookings Institute, the number of retirements in the water sector workforce is leading to staffing vacancies of up to 50%. The average age of workers in the water industry is 42.8 years, which is slightly older than the national median across all jobs, which is 42.2 years. Some areas of the water sector have skilled workers that are significantly older than the national average, such as water treatment plant operators, who have an average age of 46.4 years. The U.S Bureau of Labor Statistics (BLS) estimates that each year from 2016 to 2026, about 10.6% of workers in the water sector will either retire or transfer out of the field (Kane & Tomer, 2018).
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