The Digital Quality Management Landscape
Broadly, Industry 4.0 refers to advances in manufacturing accompanying the widespread adoption of technologies like IoT, cloud storage/computing, and AI, among many more.
These technologies have had a significant impact on quality assurance (giving rise to the name Quality 4.0), and they promise to make quality management systems more robust, easier to implement, and more cost effective to enforce.
Industry 4.0 QMS solutions fall into two partially overlapping camps.
- QMS software suites
- Digital solutions that simplify the constituent parts of a QMS (e.g. documentation, training, reporting)
QMS Software Incumbents
For many years, specialized software suites have helped manufacturers automate some of the more labor intensive aspects of QMS. These programs are usually designed to ensure compliance with FDA, FAA, or other regulations, as well as particular ISO guidelines.
These software systems excelled at streamlining repetitive processes, centralizing documentation into a single source of truth, and ensuring adherence to necessary regulations and guidelines.
They weren’t perfect, however.
Many software solutions required complicated, IT intensive integrations. Getting a piece of QMS software to communicate with a factory’s machines was itself an expensive, time-consuming task. Integrating a QMS with an ERP or CRM added new complications for both operations and data storage. Once configured, these systems could be extremely rigid, requiring IT intervention to make small changes in procedures or data accessibility. The cost and complexity of these systems limited them to larger manufacturers who could afford and sustain significant investments in quality-focused software.
In the last ten years, developments in technology and demand among SMEs have birthed more flexible QMS software. These solutions are often cloud-based, alleviating the need for expensive, on-premise integrations. The SaaS business model has created modular solutions, for which companies can pay per use-case and feature, as opposed to purchasing an entire system. And more attention has been placed into designing systems that scale.
For the modern manufacturer, there are an increasing number of viable software solutions.
New Digital Solutions
Beyond software, there are a host of new digital technologies with quality management systems. Rather than operate as a single software system, they function as part of a technological ecosystem.
The technologies in this category are easy to deploy, flexible, and customizable to a manufacturer’s operations. Rather than cover all aspects of a QMS, they attack some of the more onerous processes and components.
Modular solutions for quality management at every step
Interactive Digital SOPs – One of the most difficult aspects of compliance is ensuring that operators follow standard operating procedures to the letter on every run. Often, SOPs for a single process can number into the dozens of pages. Even if operators follow them exactly, errors are still possible, and recording their progress can reduce efficiency.
Increasingly, manufacturers are opting for media-rich, digital SOPs. These SOPs are dynamic and interactive, allowing engineers to embed video and images for complicated steps. With IoT systems, break-beams, light systems, and other interactive tools can integrate with these SOPs. These engage operators, and guide them through complex processes, making it impossible to make a mistake. Further, in-line quality checks like scales, calipers, and cameras can be used to catch non-conformances at the source.
All of this results in processes that are completed correctly a higher percentage of the time, with simplified documentation to prove it.
Media rich digital SOPs make instructions easier to follow and ensure quality in-line
Interactive Training Platforms – One of the most important aspects of a QMS are training programs. Especially for industries with high seasonality, turnover, or especially complex assemblies, it’s important that workers are trained effectively and quickly.
Fortunately, new technologies are increasingly being used to train employees. Just like digital SOPs, there are now digital applications that guide workers through pre-designed training programs, preventing the labor lost when operators are taken off the line to mentor new hires, and reducing the overall time spent training. On the vanguard, technologies like computer vision are being used to train workers on new processes as they perform them. These hands-free training systems build embodied knowledge of a task as the worker completes each step.
Ultimately, better trained employees are less likely to make mistakes, and more likely to produce quality products the first time.
Electronic Logs – Another compliance driven use of Industry 4.0 tech is Electronic Logbooks. These digital logs make it easy for an engineer to record and integrate data from equipment, machines, processes and operators. Using IoT connectivity and cloud storage to record and store data from multiple sources, they provide visibility into the state and usage of equipment in a factory. They place events, reason codes, notes, and photos into a single log, and eSignatures allow operators to verify that the information is correct at the source. These logbooks reduce the amount of time spent recording and archiving processes by hands, and places data in a single, easily accessible location.
Tulip’s eLogbook App
Improved product traceability – Demonstrating quality requires tracking materials from the supply chain, into inventory, through the manufacturing process, and through distribution to the consumer. IoT technology has made it easier to track items from end to end, bringing the ideal of complete traceability. Manufacturers now have access to a variety of tools that help them track materials and products through the full value stream. On the horizon, technologies like blockchain have the potential to create public, immutable records of a product from supplier to consumer.
But we need not look to the future. Existing product tracking technologies, when paired with other tools, like Electronic Logbooks, manufacturers are one step closer to achieving demonstrable, reportable product genealogies.
Advanced Statistical Process Control – Quality engineers have long used statistical process control to understand and analyze the variability inherent in many manufacturing processes. One of the defining features of Industry 4.0 is more data describing a greater number of features in a factory. With advances in machine learning, artificial intelligence, and big data analytics, decision-makers can leverage this data to reduce defects, and lower cost-of-quality.
Big data and Advanced Analytics – Big data has uses beyond SPC. When paired with artificial intelligence and machine learning, this data has the potential to reveal new sources for quality improvement, and to support previously unthinkable leaps in quality management. Manufacturers are already using Big Data to identify and correct bottlenecks, improve traceability, hone KPIs, improve workflows, and nuance error categories. With truly massive quantities of data now available to manufacturers, the ideal of predictive maintenance is closer than ever to becoming a reality.
These are just a few of the most significant use cases for Industry 4.0 technology within quality management systems. Manufacturers looking to reduce the burden of compliance, as well as those who are looking to realize cost savings and improved efficiency, should consider what features of their current operations could be improved. Likely, there are flexible new technologies that can amplify their quality initiatives.
This may be obvious for the industry that turned continuous improvement into a science, but it bears repeating: a digital transformation is not something that happens once. Disruption is now the status quo. Staying successful means building agility into the foundation of a manufacturing operation.