P & A Industrial Fabrications, located in Roxboro, NC, manufacturers premium woven fabrics, primarily paint roller fabric. NCGrowth analyst Anirudh Shenoy, a master’s student in Industrial Engineering at NCSU, worked with P & A to help streamline their plant processes.
P&A Industrial Fabrications in Roxboro is a manufacturer producing premium woven fabrics. They primarily make paint roller fabrics for companies such as Sherwin Williams, and fabrics for automobile manufacturers like BMW and Mercedes-Benz. P&A has about 45 employees, with all of its products being made in the USA. P&A’s central philosophies are rooted in Lean Manufacturing principles and every employee participates in multiple 5S, Lean, and Kaizen events annually.
Over the summer NCGrowth completed three projects for P&A. The first was a Kaizen event to reduce labor costs at the finishing stage of the process line. “Kaizen”, a Japanese word, means “Continuous Improvement”. During a Kaizen event, a cross-functional team is formed to improve the efficiency of a section of the process line. In preparation for the event, Anirudh simulated all the operations in a discrete event simulator to collect baseline data. During the week-long event, a team of upper-level management and machine operators first analyzed the problem by simply observing day-to-day operations. Several time-studies were performed to record the time taken to complete each task by an operator at the finishing stage. Next, a brainstorming session, where everyone looked at improving every aspect of the process, was held. The final step was to make these improvements to the process and to train operators in the new operating procedure. While it is too early to study and calculate the long-term impact of this event, the short-term impacts are significant. The total distance that an operator walked per day was reduced by 1.2 miles (a 22% reduction). This reduction in non-value added time not only makes the operator more efficient but reduces physical stress.
The second assignment was to reduce the waste and decrease the consumption of yarn in the heat-set and finishing process. In an initial study, P&A found that during the heat-setting process, the yarn shrinks considerably more than expected. This requires the fabric to be brushed more in order to maintain fabric quality. As a result, the process generates considerable waste in the form of lint and excessive consumption of yarn. To remedy this issue, Anirudh and his team at P & A, collected several samples of different styles of fabric and generated a mathematical model of the process. This allowed them to predict the extent of yarn shrinkage before the start of the process, and thereby optimize the temperature of the oven. The implementation of the solution is underway and is expected to reduce the amount of waste by over 70%.
The final project was to streamline production scheduling. P&A has been moving towards a Lean production scheduling algorithm over the past couple of years. The new scheduling program would help reduce inventory and shorten lead times significantly. Under the old system, the plant manager would spend hours every fortnight rewriting the production schedule into a format that would allow him to run the fabrics through the process line. To save time, Anirudh automated this process by writing a program in Python that reads the schedule and formats it. The new system performs the same task in less than 10 seconds. Over the summer, Anirudh also data mined the production database using R programming. He has been able to identify some patterns and created visuals using historic data that have helped the management get a holistic view of the finishing process.