Imagine this scenario: a patient undergoes hip surgery, only to be told that the replacement product that was installed inside of his or her body must be recalled due to a defective feature. Months, or perhaps years, of grueling rehab are compromised due of a lack of statistical data that could have prevented such instances from occurring.
About one out of every eight patients, or 12-13 percent who received a certain brand of metal hip have had to face corrective surgery five years after their initial procedure. This is due to a buildup of metallic particles in the bloodstream, caused by the friction of metal rubbing against metal. While not everyone is affected, some patients experience fluid buildup in surrounding joints and muscles, which can lead to bone and nerve damage.
When it comes to product recalls that damage our health and well being, it further heightens the call for companies to use statistical process control to monitor the quality of production output. Statistical process control refers to the collection and analysis of manufacturing data with the intention of improving product quality. By implementing statistical process control, the goal of eliminating or greatly reducing costly product recalls is realized. This is done by analyzing manufacturing data as it happens so that problems are stopped as they happen—instead of being caught after deployment.
By stabilizing a production process and reducing the amount of variations in productivity, both the consumer and the company benefit. The consumer benefits by receiving a safe and tested product, and the company benefits by avoiding the costs and embarrassment associated with a recall.
Additionally, statistical process control reduces the amount of money that your company is wasting on excess material during production, whether it is scrap, giveaway, rework or warranties.