Does Your Quality Control System Actually Control Quality?

Does Your Quality Control System Actually Control Quality

To prevent rework and its associated risks, a proactive approach to quality is needed.
IoT is the solution.


Let’s face it: the term “quality control” can be misleading. Quality control (QC) exists to ensure that a final output meets a set of requirements. In reality, QC is a reactive function that has minimal control over the quality of the final output.

QC is a process that becomes involved if (and when) corrective action is required on sub-par output. It follows that a more accurate name would be “quality review.”

The reactive nature of modern QC is no fault of QC professionals. QC professionals are overwhelmed with a laundry list of items to verify on a daily basisーthey are already spread thin. On top of that, they aren’t typically called out for inspection until the job is already complete. 

In order for quality control to actually control quality, a smarter, more proactive approach is needed. Without it, mistakes will always be made…but more on that later. First, let’s start with the basics.


What is Quality Control?

QC refers to the procedures and processes that exist to fulfill quality requirements and facilitate a quality output that meets all specified requirements.

These requirements can be imposed internally (such as standard operating procedures), by clients or customers, or by a third party organization or government body (such as ISO or OSHA).

Quality control should not be confused with quality assurance (QA). QA confirms that the manufactured output meets each set of requirements, while QC is the inspection of these elements. 


Ineffective Quality Control is Causing Rework

No point better underscores the QC fallacy than rework. Rework occurs when work is not done correctly the first time, and it must subsequently be redone or corrected.

According to a recent Autodesk/FMI study, correcting poor work quality costs construction companies and their customers about $625 billion every year. Specifically, an estimated 6% of total project cost goes toward rework on a typical project.

In addition to causing significant budget and schedule problems, rework is also a major safety hazard. A worker is 70% more likely to be injured performing rework than planned work. Rework causes 39% of all workplace injuries in construction, impacting more than 1 million construction workers and their families each year.

The current quality control process exacerbates the rework problem. We cannot prevent rework if we wait until the end to check whether work was done correctly.


A Proactive Approach to Quality Control 

Converting QC from a reactive to a proactive approach may seem daunting. After all, current QC practices have evolved over decades and changes are viewed skeptically by practitioners. However, the solution is easier than you might think, and does not actually require a significant change to the way work is performed.

The Internet of Things (IoT) allows us to think about quality control in a whole new way.

IoT is a set of physical objects that are interconnected via sensors, communication systems, and software. This is one of the most important technological innovations in recent history, since it now allows for the connection of everyday objects一like doorbells, thermostats and watches一with the Internet.

You might be wondering: how exactly can IoT create a more proactive quality control system? Glad you asked. Much of the benefits that can be derived from IoT center around the use of IoT tools and sensors while performing critical manual work.

For example, the first application of the Cumulus system was managing the assembly of critical bolted connections with digitally connected tools. Cumulus monitors work quality in real time by collecting data from these connected tools using a Bluetooth connection and validating that assembly is performed correctly.  This ensures that bolted connections are never under or over-torqued during assembly. This helps ensure work is performed correctly the first time, every time.

In short, IoT allows for quality problems to be detected at their source and in real-time, shifting quality control from a reactive to a proactive approach.


The Benefits of an IoT-Centered Approach

The benefits of integrating IoT into manual work activities don’t stop there. While flagging quality problems at their source is a big selling point, IoT also has the ability to drive more productive practices, reduce time spent on work completions, and, most importantly, ensure the safety of both workers and end users. 

The benefits of using IoT technology in a quality control capacity include:

  • Quality: Organize data from connected tools onto a real-time dashboard to ensure work adheres to quality standards 
  • Productivity: Provide workers with real-time project info and step-by-step instructions so they never have unplanned downtime
  • Sustainability: Reduce paperwork on work completions and eliminate the unnecessary emissions associated with leaks and rework
  • Reputation: Elevate your company and project’s reputation by delivering on time and on budget
  • Safety: Eliminate rework and reduce exposure hours via streamlined work and reporting procedures


How To Evaluate Your Quality Control System


How To Evaluate Your Quality Control System | Cumulus Digital Systems

Before implementing any new technology, it’s important to first understand the pain points associated with your current system. This will allow you to seek out the right solution based on your project’s needs and avoid the pitfalls associated with simply choosing the splashiest new technology.

The first step in this process is discerning the shortcomings of your current quality control system. This can be difficult because problems that arise are often far removed from the cause of the problem. For that reason, root cause analysis can be a helpful tactic for tracking problems back to their source.

To evaluate your current quality control system and determine next steps, use the following framework:

  1. Define the current requirements. What quality control standards are currently required? If you don’t already have one, develop a comprehensive list that includes regulations from third parties, specifications from customers, and internally imposed standard operating procedures. The list should be comprehensive.
  2. Determine the results. What results have been achieved under your current system? Track the metrics that are most important (or detrimental) to your company. This could include successful work completions, amount of rework, percentage of work completed on time and on budget, worker turnover, etc.
  3. Identify patterns. Once you have specified your current requirements and the results achieved under that system, it’s time to identify patterns in your data. This will help you to pinpoint your specific problems and determine where you need the most help. Pay specific attention to the quality failures and the circumstances surrounding those issues. 

The final result should be a list of your project’s main challenges that cause most of your quality issues. This valuable information will allow you to seek out the right technology solution to improve work quality and productivity. 


Make The Right Quality Decisions with Cumulus 

With Cumulus technology, enable a single source of truth for quality assurance and progress tracking. Schedule a demo to get started.