Real-time Digital Manufacturing: Realized
Global Recruiters of Palmetto (GRN) Automation Recruitment Specialist
Three golden rules for accomplishing success: attract talent, hire talent and keep talent. It is that simple.
Source: Automation.com
Worldwide manufacturing had a wake-up call with the pandemic and supply chain disruptions. Outsourcing for lower costs has created pain and is a pressure point with negative impacts both on sales and on increasing profitability risk. However, the foundations of manufacturing and production are being reshaped by the integration of manufacturing production into the entire industrial business system. A digital manufacturing architecture offers a streamlined approach to enterprise-wide clarity that allows stakeholders to adjust operations based on real-time insights, i.e., data transparency.
Worldwide industrial digitalization
The impact of open manufacturing initiatives continues to advance worldwide as countries and industries recognize the need to modernize with Industry 4.0, and other related initiatives being adopted and accelerating. These provide models for all industrial manufacturing organizations to achieve holistic and adaptive open automation system architectures. Germany’s Industry 4.0 initiative ignited worldwide cooperative efforts in other countries including China, Japan, Mexico, India, Italy, Portugal?and Indonesia to apply technology to increase production competitiveness.
At the same time, the lack of investments by companies, governments?and schools in vocational and technical education is a major issue. In the decades after the Second World War, high school dropouts could walk onto factory floors all around America and find decent, secure, middle-class jobs; this is no longer the case. Companies for many years have not invested in meaningful internships and apprenticeships, further drying of the skilled labor pipeline. Certainly, unskilled labor continues to be eliminated by automation, but industry still requires skilled and knowledgeable people educated to work with new manufacturing technologies.
These trends are being helped by the rise of real-time manufacturing business systems. Digital transformation is creating an integrated real-time system from sensor to enterprise and cloud, which is now possible with the application of open standards and technology. Manufacturing and production companies increasingly are digitalizing to overcome the inefficiencies of siloed systems that create overlaps in processes and, more importantly, gaps in knowledge that stifle collaboration, efficiency?and ultimately growth.
Digital transformation is empowering companies to realize holistic manufacturing business. This is achieved with a real-time distributed manufacturing architecture (DMA).
Achieving lean, high-velocity manufacturing requires product, material?and information flow all working in concert. Information flow impacts the efficiency of a responsive manufacturing supply chain. Intelligent manufacturing systems ensure optimized, fast?and reliable product and material flow. These systems should be integrated and networked so that product/process data and business manufacturing information can smoothly “flow.” A key manufacturing competitive advantage is not how well each system works but how well they all work together.
Simplified hierarchies
Industrial automation is changing from hierarchical Purdue models to more responsive architectures, achieving the goals of integrated real-time manufacturing. I wrote about the roots of this change in 2012 in an article titled “Simplifying Automation System Hierarchies.” Now, these architectures are being deployed at a growing rate to achieve more efficient and profitable manufacturing. New technology is making it possible to streamline this model to eliminate layers, increase performance?and reduce software maintenance costs.
The traditional strict hierarchy architecture is giving way to a more responsive and direct model to create real-time highly responsive manufacturing businesses. Field devices can communicate information directly with applications including historians, advanced cloud analytics, real-time maintenance monitoring?and other functions. This simplifies the applications of these functions and eliminates Level 2 and Level 3 software costs, complexity, performance drag?and ongoing software maintenance.
Over the years, industrial automation architecture has been marked by increasing computing pushed toward final field devices, leveraging distributed computing to increase performance, quality, reliability, availability, responsiveness?and reduce software maintenance costs. The limiting factor at each step has been the cost, ruggedness?and reliability of technologies. This has changed with significant commercial, consumer?and Internet of Things (IoT) technology and communications advances at low cost that are pervasive in daily life.
The smartphone—an everyday device many people possess—is an obvious example of a rugged, powerful computer with integrated communications and display.
The most commonly used industrial automation architecture model to define manufacturing operations management is the five-level Purdue Reference Model (PRM), which later formed the basis for the ISA-95 standard. This five-layer hierarchical architecture served the industry well for years, being easily deployed with the existing available technology. The model is typically expressed as:
Traditional automation systems generally reflect this architecture with software running on general-purpose computers at Levels 2, 3, 4?and 5. Levels 2, 3?and 4 typically have database and communications interfaces that buffer and synchronize information between each level in addition to the associated human-machine interface (HMI) and user interfaces. The constraints of computing costs and networking bandwidth dictated this configuration based on past technology. The multilevel computing model is complicated, creating a great deal of cost, ongoing configuration control?and lifecycle investment. Fortunately, this model is changing to enable a more efficient and streamlined automation system architecture.
Industrial manufacturing organizations have been eliminating the barriers between functional silos that create overlaps in processes and gaps in knowledge that impede collaboration, efficiency?and, ultimately, growth. Manufacturing companies are integrating more tightly into the business, and this is also reflected by the integration of systems from sensor to enterprise. The transformation to integrated, real-time, data-driven manufacturing eliminates inefficiencies, increases responsiveness, increases profits?and encourages competitiveness.
The shift to digital manufacturing architecture (DMA) is a fundamental building block for transformation that has implications from the enterprise level to the farthest end of manufacturing and production—sensing and control devices (Figure 1). This distributed system includes applications on embedded processors in sensors, actuators, barcode readers, cameras?and other field devices that can be controlled locally, but equally important, they can also be accessed remotely for complex calculations and adjustments at any time.
This architecture allows for real-time transaction processing and synchronization with manufacturing, creating a closed loop. In addition to being highly integrated, effective DMAs:
In the new model, controllers can communicate information to all levels directly using the appropriate methods and protocols. Ethernet communication has become the high-speed and pervasive technology used by industrial automation protocols and business systems. More controllers are supporting multiple Ethernet ports to interact directly with industrial and business networks that exist throughout industrial plants. Historians, analytics, real-time maintenance monitoring?and other functions are now being incorporated into controllers.
This simplifies the applications of these functions and eliminates traditional architecture software costs, complexity, performance drag?and ongoing software maintenance. More powerful controllers and communications enable the coordination between controllers without requiring a separate computer to coordinate them as well.
The most effective architecture requires orchestrating and optimizing all elements of the process for flexibility in the face of external changes including supply chains, customer demands, costs, availability, energy?and sustainability requirements. The emerging DMA technology leverages advances in distributed computing and open systems to accomplish this and achieve synchronized, real-time, optimized production (Figure 2).
Customer orders, supply chain factors?and factory operations are fed into the digital twin, an ideal operating model of the plant and its processes. Real-time linkages throughout the system create a closed loop (Figure 3) with constant feedback, whereby analytics, artificial intelligence?and machine learning adjust and optimize operations.
Digital manufacturing architecture requirements are driving industrial cybersecurity integration with mainstream information technology (IT), cloud?and IoT protection technologies and methods to create more secure manufacturing environments. Major technological advances include the incorporation of firmware/hardware in controller intelligent sensors, actuators?and other field edge devices.
Real-time digital manufacturing is about becoming a more effective, holistic and competitive business. This increases reliability, quality, production, profitability, safety, flexibility, informed decision-making?and overall competitiveness as a business.