“Perfection is not attainable, but if we chase perfection, we can catch excellence.” ~ Vince Lombardi

Every manufacturing business will eventually encounter quality problems, but all can take steps to identify quality issues before they become serious problems. In this post, we’ll discuss why it’s important to identify quality problems early. We’ll also describe the tools you’ll need to address them effectively so that such problems don’t compromise employee or customer safety.

Why Quality Control Should Be a Priority

Putting a quality control (QC) program in place has the welcome effect of creating a “quality consciousness” among employees. With your workforce onboard, the QC program can elevate the reputation of your business, reduce waste, and the likelihood of liability claims and lawsuits. 

A solid QC program can prevent injuries to employees as well as customers. And, while some might argue that using quality control processes to address safety is time-consuming, it’s ultimately more efficient because customer complaints, defects, and recalls are far more disruptive.

A sound QC program also increases customer satisfaction by preventing defects that would disappoint customers. Customer Satisfaction (“CX”) has become incredibly important to marketers everywhere in recent years because it directly translates to greater customer lifetime values, greater loyalty, and increased referral business from happy customers.

Further, well-designed QC programs reduce waste. With automated machinery producing hundreds or thousands of a given product daily, a machinery defect can quickly force you to scrap large volumes of raw material. And, in cases where your products must comply with environmental, health, safety, or other regulations, quality control can again prevent defective products, waste, and unnecessary expense.

Adding Problem Identification to Your Quality Program

The worldwide manufacturing industry has continued to evolve from digital automation to Industry 4.0. Today, it relies on algorithms, artificial intelligence, machine learning, and IoT devices to automate nearly every aspect of countless fabrication processes. It also provides specialized tools — process mapping, for instance — that are useful in identifying problems that can affect product quality and safety. In fact, a host of approaches to problem identification includes …

  • Root cause analysis (RCA), in which you identify and describe the problem, then distinguish between the true root cause of a defect and other causal factors.
  • Statistical process control, which helps QC staff identify and solve problems while products are still in the manufacturing facility.
  • Total Productive Maintenance (TPM) improves product quality by eliminating downtime, defects, accidents — all of which fall to (or approach) zero when TPM is done effectively.
  • Kaizen is a continuous improvement approach that creates a culture where all employees work at identifying and solving problems at their source.
  • 5S, a framework of lean manufacturing adapted from Japanese manufacturing. Data collection is an integral part of 5S and can be used to identify and document problems as they occur.

Regardless of which quality control program you follow, problem identification should be a proactive effort throughout all your manufacturing processes, not just an inspection of goods as they come off the line. In fact, there are two steps you’ll need to take to optimize problem identification. They both require documentation:

  • First, outline how your team will evaluate quality throughout the manufacturing process. Define and explain the quality standards and programs you will use.
  • Second, document the training you’ll implement to teach employees how to identify defects and problems, and the procedures they will use to solve them. 

Communication Is Key in Problem Identification

Imagine for a moment you’re a product marketing manager about to launch a new product. You want to identify potential problems that can lead to defects before beginning to manufacture. Therefore, early on, you communicate product development plans to Manufacturing Engineering, to Finance, to the C-suite, and to others who have a stake in producing the new product. You want to confirm that the product will be cost-effective for the company and the customer, and that it meets company goals. Failure to communicate openly and regularly can lead to a lack of management support, which can delay or even terminate the project. 

You also recognize that achieving the quality your product deserves requires a team. Thus, your early planning and communication need to document the functional units and personnel who will take responsibility for various kinds of risks, challenges, and problems. 

Make Use of Data to Prevent Problems as Early as Possible

In this age of Industry 4.0, data and data scientists, often assisted by AI and machine learning, inform management on innumerable topics. However, the data you use needs to be relevant to the task at hand. It needs to be available in sufficient quantity so you’re not working with tiny datasets that won’t reveal meaningful guidance. And, it needs to be gathered in a structured, repeatable fashion so it can be statistically analyzed. With the right quantity and quality of data, you can closely monitor the manufacturing processes associated with your new product and identify problem areas as they’re occurring and, ideally, even before they occur.