Driving Quality – Part 1: Automotive Quality Control Procedures in the Supply Chain

David Gurr
By David Gurr | July 2, 2020
Account Manager
How can automotive component parts suppliers comply with, and gain real business advantage from, quality management frameworks? What are the best strategies for managing the key tasks in a post-COVID-19 world—and providing robust quality control in the automotive industry?
Your average modern car is one of the most complex pieces of machinery you will ever own. With around 30,000 individual components, managing the quality of component parts through the supply chain is a vital task.
It’s no surprise then that the industry has been striving to advance automotive quality control procedures for some time. Lean manufacturing principles emerged from the Toyota Production System (TPS) in the 1950s. In the 1980s, Ford, Chrysler, and GM began developing the APQP process using Statistical Process Control (SPC) and Six Sigma techniques, among others. Toyota started sharing TPS with its parts suppliers in the 1990s. Some of the main automotive-producing countries built their own quality management system frameworks in the 1990s—VDA (Germany), AIAG (US), AVSQ (Italy), FIEV (France), and SMMT (UK).
By the late 90s, the industry realized this wasn’t a viable approach. Tier 1 suppliers supplying vehicle manufacturers—or original equipment manufacturers (OEMs) in industry parlance—were often supplying automotive manufacturers in different jurisdictions. Tier 2 suppliers—those supplying the Tier 1s—were in an even more complex situation.
SPC in the automotive industry

Automotive Quality Control & Standardization

The first attempt at rationalizing the situation was the ISO technical specification ISO/TS 16949:1999, revised over the years to ISO/TS 16949:2009 and later reworked as IATF 16949:2016. These standards were built on the more general ISO 9001 Quality Management System framework, with extensions. Some of the most demanding requirements are in measuring and monitoring the production process itself—Chapter 8 in the 2009 standard (“Measurement, Analysis & Improvement”) and Chapter 9 in the 2016 version (“Performance Evaluation”).
Both versions of the standard include a common set of requirements for automotive quality control management in production processes:
  • Measuring and recording each variable for each process in a reliable, repeatable way and assessing the variation and capability of the processes by means of a control plan
  • Use of statistical tools as part of the control plan (statistical process control, or SPC)
  • Having corrective action plans to return processes to stability that are triggered on key conditions
  • Recording when those events are triggered, the causes of those events and the corrective actions taken
  • Having the ability to perform long-term analysis of the relative prevalence of assignable causes and corrective actions to aid process improvement
Initially, many suppliers viewed the standard as a compliance issue—a necessary hoop that had to be jumped through in order to continue to do business with their customers. The goal was often simply to just have enough of a business process to satisfy an auditor. Those business processes would be implemented by forms, forms, and more forms—as manual processes. Because manual processes are cheap, right? And paper forms are easy!
Standardization in the Auto Industry requires statistical process control analysis

Real-Time Statistical Process Control Analysis

Clearly, that didn’t work out so well. Suppliers in the automotive manufacturing industry found that complex manual processes were taking more and more time away from the business of actual production. Forms need to be maintained, distributed, version-controlled, transcribed, archived, and stored. Intangible costs are still, after all, costs.
The smarter suppliers quickly realized that there was an alternative. Instead of treating the standard as a compliance issue, could the principles in the standard actually produce a real business benefit? The closer they looked, the more they realized that was the case.
Through careful monitoring of process variation and capability, suppliers realized they could dramatically reduce their scrap and rework costs, as well as customer complaints. But to do this effectively, they’d need to collect and analyze their metrics in real-time. Also, by analyzing trends in key conditions and the application of reaction plans and corrective action plans, they could see “hot spots” in their business and bring appropriate resources to bear.
Optimizing Manufacturing Processes for Quality SPC

Introducing Enact

But they wouldn’t be able to achieve this with simple forms and manual processes. For more effective automotive quality control, manufacturers are increasing adoption of digital transformation. Under the Industry 4.0 framework, physical manufacturing processes are being increasingly integrated with advanced information technologies and services—from data collection and real-time monitoring to advanced analytics capabilities.
This union of the physical and digital realms is being leveraged to achieve levels of manufacturing optimization that are becoming a critical operational imperative in an increasingly dynamic and competitive industry sector. Enact®, the Quality Intelligence platform from InfinityQS, is designed to achieve exactly this.
Enact Quality Intelligence Platform
Enact Quality Intelligence Platform

How Enact Improves Automotive Quality Control Procedures

Enact helps automotive manufacturers collect all their SPC data and quality-related metrics into a single version of the truth, in real time, no matter how or where they are generated. Whether from manual tests by operators, from batch operations via CMM, or from unattended in-process devices or sensors, Enact can collect all data in real-time into a single database.
Enact also allows you to define the events on which you want to trigger an action plan. These can be compliance events (something did or didn’t happen), limits (something was out of specification), or statistical events (some significant pattern occurred in the data). You can define mandatory actions and optional actions, and track who these are completed by, and when.
Enact workflows for quality control 
Event Pareto chart details
Sample Enact Workflow images - Event Details and Pareto Chart (click to enlarge)
Then, Enact enables different audiences to view different analyses of this data—in real-time, without waiting for reports. Each audience can see the analysis that matters to them, based on physical scope (location, or groups of parts, or processes) and time (short-, medium-, or long-term). What’s more, each user can then ask questions of that analysis and get the answers—instantly.
That analysis is presented in a way that allows you to “roll up” data—so you can easily find out, for example, which shift has the biggest process variation? Or which line or machine? Or which plant? Or even which country? And you can then “drill down” to find out why.
Enact Analysis SPC Dashboard
Sample Enact Analysis dashboard

There’s Always One More Thing…

So now you can avoid wasting time on non-productive form-filling and manual compliance systems and focus on the real job—producing the best quality products in the most efficient way possible.
Problem solved—until a little thing called COVID-19 came along and ruined the party. Now, we need to work out how to do all the above while maintaining safe social distancing. Luckily, Enact also helps there—and that’s the subject of Part 2 of this blog series. Read the other articles in this series:  
Take advantage of the technology at your fingertips today: contact one of our account managers (1.800.772.7978 or via our website) for more information.
Contact your local Enact Channel Partner.

InfinityQS Fact Checking Standards

InfinityQS is committed to delivering content that adheres to the highest editorial standards for objective analysis, accuracy, and sourcing.

  • We have a zero-tolerance policy regarding any level of plagiarism or malicious intent from our writers and contributors.
  • All referenced articles, research, and studies must be from reputable publications, relevant organizations, or government agencies.
  • Where possible, studies, quotes, and statistics used in a blog article contain a reference to the original source. The article must also clearly indicate why any statistics presented are relevant.
  • We confirm the accuracy of all original insights, whether our opinion, a source’s comment, or a third-party source so as not to perpetuate myth or false statements.



Never miss a post. Sign up to receive a weekly roundup of the latest Quality Check blogs.