Anyone engaged in digital transformation efforts must understand how smart manufacturing deployments can produce the intended quality outcomes on the manufacturing floor. According to Rockwell Automation’s 9th Annual State of Smart Manufacturing survey, “Improved quality is the number one outcome respondents hope to achieve from existing smart manufacturing technology,” beating out cybersecurity, process optimization, and supply chain management. Quality is paramount, because it offers numerous benefits, including reduced risk and cost, increased compliance and customer satisfaction, and continuous improvement.
The practice of quality in the context of digital transformation and Industry 4.0 is known as Quality 4.0. This practice utilizes advanced technologies to achieve quality outcomes, while also enhancing efficiency, productivity, and data-driven decision-making. While discussions of digital transformation, Industry 4.0 or Quality 4.0 often focus on technology as the driver of these outcomes, people and processes are also critical elements. Technology has always been in service to people and process, and it is through their combined efforts that organizations can fully realize the benefits of Quality 4.0.
As long as quality is an important outcome for digital transformation, implementing Quality 4.0 will be critical for those driving digital transformation efforts. This blog will explore how technology, people, and process come together to build the practice of Quality 4.0 on the manufacturing floor. It will also look at how Quality 4.0 aligns with and enhances the goals of digital transformation.
Understanding Quality 4.0
The quality discipline has always evolved in the context of technology, and like technology, it is evolving still. As Industry 4.0 builds on the technical innovations that came before it, Quality 4.0 builds on traditional quality management principles and best practices, such as standardization, continuous improvement, and total quality management.
Whereas Industry 3.0 was characterized by digitization, or moving from physical information formats to digital ones, Industry 4.0 marks an era of “digitalization,” which utilizes integrated systems, connectivity, and vast data sets to enable real-time visibility into processes, data-driven decision-making, and collaboration across the value chain by removing silos within and beyond the organization. In Quality 4.0, these technical innovations enable predictive quality management, real-time monitoring, increased standardization, and supplier quality assurance. Importantly, they also enable workers to focus on higher order tasks, improve decision making, and create stronger feedback loops.
Quality 4.0 technologies
Let's start by examining the technologies that facilitate Quality 4.0. These advanced technologies are pivotal for any manufacturing company looking to navigate the complexities of digital transformation, as they provide deeper insights into product and process quality and enable more accurate predictions and timely interventions. From AI to advanced data analytics and beyond, the technological backbone of Quality 4.0 enables companies to achieve superior quality standards and operational excellence in an increasingly competitive market.
- Advanced automation: Technologies such as AI, ML, IIoT, and robotics perform tasks with minimal human intervention, reducing human error and increasing standardization. AI and ML analyze data to predict failures and optimize processes, while IIoT integrates connected devices for real-time data collection and predictive maintenance. Robotics, including collaborative robots, enhance productivity and ensure precision in repetitive tasks, enabling real-time quality control and freeing humans for more skilled activities.
Advanced data management: Technologies such as blockchain, big data analytics, and cloud computing provide data-driven insights that support predictive maintenance and enable continuous improvement through detailed performance monitoring.- Advanced manufacturing: 3D Printing, CNC Machining, and advanced fabrication technologies enable the efficient and precise production of complex parts and products. Also known as additive manufacturing, 3D printing supports rapid prototyping, iteration, and testing under real-world conditions to ensure quality standards before mass production.
- Digital thread: The technologies of computer-aided design (CAD) and product lifecycle management systems (PLM) form the foundation of the model-based enterprise (MBE). Integrating CAD and PLM with other model-based systems compounds the quality benefits of the MBE on the shop floor and beyond.
- Computer-aided manufacturing (CAM): These systems enable the seamless translation of CAD models into machine instructions, ensuring that manufacturing processes adhere to design specifications.
- Manufacturing execution systems (MES): These systems provide real-time monitoring and control of production processes. By integrating with predictive analytics, MES allows for predictive quality control, enabling early detection of potential issues and proactive adjustments to maintain standards.
- Model-based work instructions (MBWI): MBWI supports Quality 4.0 by providing visual, interactive, and dynamically updated guidance for assembly, maintenance, and training. These instructions facilitate better comprehension, collaboration and feedback among team members, ensuring that everyone is aligned with quality standards and procedures.
- Digital twins: Digital twins create a virtual replica of physical assets on the manufacturing floor, which helps in simulating, predicting, and optimizing the system performance without interrupting the actual production process.
The effectiveness of digital thread technologies like model-based work instructions (MBWI) highlights the critical role of people in Quality 4.0. While advanced tools and systems provide the necessary framework and data, it is the people who interpret, implement, and refine these instructions to drive continuous improvement. Empowering employees with the right skills and fostering a culture of collaboration and learning ensures that these technologies achieve their full potential.
People in Quality 4.0
- Leadership commitment: Effective Quality 4.0 initiatives start with strong leadership commitment. Leaders must champion quality as a core organizational value, allocate necessary resources, and drive the adoption of digital tools and technologies that enhance quality management. Their support is crucial in creating a culture that prioritizes quality and continuous improvement across all levels of the organization.
- Skilled and empowered employees: Employees need to be equipped with the skills and knowledge to leverage advanced digital tools effectively. Continuous training and development programs are essential to keep the workforce up to date with the latest technologies and quality management practices. Empowered employees who can make data-driven decisions and collaborate effectively contribute significantly to identifying and resolving quality issues proactively, ensuring consistent and high-quality outcomes.
By putting people at the center of Quality 4.0, organizations can harness the full potential of digital transformation. A committed leadership and a skilled, empowered workforce are critical in driving quality initiatives and achieving sustainable excellence. This human-centric approach ensures that technological advancements are effectively utilized, fostering an environment where quality is continuously improved and upheld.
Process in Quality 4.0
Equally important to Quality 4.0 are the processes that support and enhance the role of people and technology. Some process principles have been important to the quality discipline for decades, such as standardization, lean, and continuous improvement. However, the implementation of advanced technologies has enabled the emergence of newer process principles that further optimize quality outcomes.
- Agility and flexibility: Processes must be designed to be agile and flexible to adapt quickly to changes in demand, technology, and market conditions, while maintaining high standards.
- Collaborative and cross-functional approach: Collaboration between different departments and functions should be encouraged to address quality issues comprehensively, ensuring that quality is a shared responsibility across the organization.
- Real-time monitoring and control: Systems must provide continuous, real-time visibility into manufacturing processes, enabling immediate detection and correction of quality issues to reduce downtime and improve overall product quality.
- Predictive analytics and maintenance: Predictive analytics foresee potential quality issues and equipment failures before they occur, allowing for proactive maintenance and process adjustments that prevent defects and ensure consistent quality.
- Data-driven decision making: Decisions are based on comprehensive data analysis and insights rather than intuition, enhancing accuracy and effectiveness in quality management for better outcomes and continuous improvement.
Conclusion
As manufacturing companies navigate the complexities of digital transformation, implementing Quality 4.0 is essential for achieving superior quality outcomes. Quality 4.0 integrates advanced technologies, skilled and empowered people, and optimized processes to drive continuous improvement, enhance decision-making, and foster collaboration across the organization. By placing people at the center of these efforts, companies can ensure that technological advancements are effectively utilized and that quality becomes a shared responsibility. Focusing on these key elements allows organizations to harness the full potential of digital transformation, delivering exceptional quality and operational excellence.
Learn about how model-based work instructions drive quality on the manufacturing floor during our upcoming webinar, "Elevate Quality with Model-based Work Instructions." The 30-minute session will be held Thursday, July 11 at 1 PM EST. If you can't make it live, register anyway to get access to the on-demand recording as soon as it's available.
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