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In today’s rapidly evolving advanced manufacturing landscape, the drive for efficiency, precision, and quality is more critical than ever. Autonomous Process Control (APC) stands at the forefront of the smart factory transformation, offering a cutting-edge approach that leverages robotics and automated inspection technologies to achieve consistent, high-quality production without the need for human intervention. As the core capability of fully autonomous manufacturing, using robotics to achieve APC is not just a technological advancement - it’s a foundational methodology for automation-intensive companies seeking to achieve six sigma quality for greater yields and profitability.

Table Autonomous Process Control: Immediate, Near-Term, Long-Term
Image Source: Flexxbotics

The Shift to Autonomous Manufacturing

Over the last few decades, manufacturing has seen significant advancements, primarily driven by automation, robotics and digitalization. Conventional factory operations, which rely on skilled engineers and operators, are now shifting toward ever greater levels of autonomy. This evolution is largely due to the increasing use of robotics and digital solutions, which are essential in addressing the economic pressures associated with reshoring, supply chain restructuring, and labor shortages.

APC plays a pivotal role in this shift particularly in automation-intensive industries such as automotive, electronics, and consumer goods and sectors with significant compliance requirements like aerospace, defense, and life sciences. By automating production adjustments based on real-time inspection results, robot-enabled APC enhances precision, reduces waste, and can decrease the cost of quality by 20% or more. For manufacturing and quality executives, understanding and implementing robotic APC production is crucial to staying competitive in a world where automation is rapidly becoming the norm.

The Challenge of Consistency in Advanced Manufacturing

Achieving consistent quality and yields in unattended operations has always been a significant challenge in advanced manufacturing. Variability in processes can lead to inconsistencies in product quality and reduced production efficiency. As manufacturing systems grow more complex with higher levels of automation, the need for scalable, repeatable processes becomes increasingly urgent. APC addresses this challenge head-on by integrating production robotics with autonomous capabilities, ensuring higher precision and consistency, which translates into greater profitability.

The Importance of Robot-enabled APC in Modern Manufacturing

Autonomous Process Control (APC) is essential for achieving Industry 4.0’s vision of “lights-out” manufacturing where production robots can make quality products indefinitely without human involvement. As automation levels increase in smart factories, the ability to produce high-quality parts autonomously becomes critical. Without APC in place, achieving fully autonomous production is not feasible. APC, therefore, represents the cornerstone condition that must be attained to realize the promise of autonomous manufacturing.

The Objectives of Autonomous Process Control using Production Robotics

The primary goal of robot-enabled APC is to bring about new levels of precision, quality, and efficiency in unattended operations. The key objectives include:

  1. Achieving Repeatable Production: Utilizing robotic automation for APC enabled by standard digital software to ensure consistent production outcomes.
  2. Ensuring Precision Quality: Achieving high levels of product quality autonomously through APC without human intervention.
  3. Improving Compliance & Traceability: Comprehensive APC data collection and revision tracking to provide digital thread traceability with quality records for compliance, especially important in regulated environments.
  4. Increasing Yields and Improving Margins: Optimizing processes using APC to enhance production yields and profit margins.
  5. Enabling Autonomous Manufacturing: Attaining APC as the foundational capability necessary for fully autonomous manufacturing.

How APC Works: Methodology and Technology

Autonomous Process Control (APC) is made possible through a combination of modern robotics, machine-based inspections, and smart factory digitalization software. At its core, APC enables robots to autonomously adjust production processes based on real-time data from automated inspection technologies and other sensors. This closed-loop system ensures continuous monitoring and proactive corrections, leading to consistently high-quality production without human involvement.

Key Components of APC Technology:

  • Production Robotics: This includes both industrial robots and collaborative robots (also known as power & force-limiting robots).
  • Automated Inspection Technologies: These involve machine-readable feedback sources such as probes, sensors, vision systems, telecentric measurement equipment, coordinate measuring machines (CMMs), and other automated input sources.
  • Standardized Digital Software Solution: Essential solutions capabilities include bi-directional interoperability communication between robots and various machines to orchestrate factory equipment, collecting and analyzing big data, and statistical process control (SPC) with algorithmic calculation and decision-based logic.

Steps for Implementing Robot-enabled APC

Implementing APC in a manufacturing environment involves several fundamental steps:

  1. Define Business Goals: Before starting any APC initiative, it’s important to identify the business case and desired business outcomes.
  2. Quality Planning: Define the critical product characteristics, tolerances, and compliance requirements, focusing on in-process or in-line inspections.
  3. Processing Design: Map out approaches and select appropriate automated inspection technologies based on the type of inspection, conditions, and required accuracy.
  4. Robotic Digitalization: Configure robots, machines, and inspection equipment, and integrate them with the standardized digitalization software solution for orchestrating closed-loop APC processes.
  5. Validation and Optimization: Conduct first article inspections, verify APC control limits, establish processing requirements, and scale up production with iterative adjustments.

It is important to note that no prior data are required to implement APC, and there is no artificial intelligence training necessary to achieve APC.

Best Practices & Pitfalls in APC Implementation

Best Practices:

  • Regular calibration of inspection equipment is essential to maintain APC accuracy.
  • Continuously monitor and adjust quality plan based on APC-enabled processing results.
  • Perform periodic optimization reviews to identify APC processing improvements.

Common Pitfalls:

  • Relying on final inspection for APC - instead of multiple in-process or in-line inspections - resulting in feedback loops that are too long for effective processing adjustments.
  • Attempting to utilize multiple legacy IT systems to enable APC resulting in integration complexity and ineffective implementation.
  • Creating custom system software that is unsustainable and cannot be extended to new machines, robots, or inspection equipment limiting factory flexibility.

The Benefits of APC: From Accuracy to Profitability

Robotic-enabled APC offers a range of benefits that can transform manufacturing quality operations:

  • Greater Accuracy and Precision - APC reduces variability for improved consistency resulting in higher levels of quality.
  • Defect Reduction - APC provides better nonconformance capture and avoidance to reduce defects by more than 30%.
  • Yield Improvement - APC optimizes processing to increase production yields between 25-45% depending on the nature of the process.
  • Improved Quality Control - Fewer bad part escapes resulting in greater control and compliance.
  • Tighter Feedback Loops - Autonomous real-time processing adjustments maintain quality specifications and standards.
  • Reduced Scrap & Rework - Decreased amount of scrap and rework resulting in less value-add waste and lower material cost.
  • Reduced Cost of Quality - Reduced cost of quality by 20% or more leading to higher profit margins.
  • Enhanced EBITDA - Improved earnings before interest, taxes, depreciation, and amortization (EBITDA) through lower manufacturing costs, higher productivity, and greater profit per part.

Looking Ahead: The Future of Robot-enabled APC

As automated manufacturing continues to evolve, the future of robot-enabled APC will become even more technology-intensive. Continued advancements in inspection technologies will allow for even greater precision in measurements. Additionally, the incorporation of machine learning and artificial intelligence for adaptive algorithms could further enhance APC’s capabilities, enabling self-learning process control systems that are even more efficient and effective.

Conclusion: The Path to Autonomous Process Control

Autonomous Process Control (APC) is the cornerstone of achieving fully autonomous manufacturing. By leveraging the power of robotics and automated inspection technologies enabled by a standard digital software solution, APC can deliver repeatable, precision-quality production with greater than 30% defect reduction without human intervention. The benefits of APC - ranging from improved product quality to enhanced profitability - make it a vital investment for any quality-oriented manufacturing operation looking to stay competitive in an increasingly automated world.

Executives in quality and operations, as well as, personnel at all levels seeking to understand and implement APC in their factories worldwide should develop an APC strategy to stay competitive in increasingly automated environments. Steps to initiate an APC implementation include assessing current capabilities, investing in necessary technologies, and developing a plan for roll-out and optimization. The smart factory future is autonomous, and robot-enabled APC is the key to unlocking its profits.

References

[1.] T. Bouchard, T. Modelski, “Autonomous Process Control (APC) using Robots and Automated Inspection in Manufacturing,” 2024.