I first heard about the Open Manufacturing Platform during my last trip to Germany, well, my last business trip anywhere, last February. I wrote about it here–Open Manufacturing Platform Expands.This effort, led by Microsoft and BMW joined by ZF, Bosch, and ABInBev, “helps manufacturers leverage advanced technologies to gain greater operational efficiencies, factory output, customer loyalty, and net profits.” That’s a tall order. These are companies that I’ve seen leverage technology for improvements over the years. This should be an advancement.
This month’s news items (2) relating to OMP include NI through its recent acquisition Optimal Plus joining the organization and a new deliverable from the OMP’s working group.
NI says that it has joined OMP “with the goal of establishing an architecture and standards for auto manufacturers to better leverage and automate analytics to improve quality, reliability and safety.”
I had an opportunity to interview Michael Schuldenfrei, NI Fellow and OptimalPlus CTO about smart manufacturing, what OptimalPlus adds to NI, and OMP. The roots of OptimalPlus lie in enterprise software relative to manufacturing of semiconductors. An early customer was Qualcomm who used the software to collect and analyze data from its numerous manufacturing plants. It branched out into assemblies, such as with a new customer Nvidia. Later the company added mechatronics to its portfolio. That was a good tie in with NI.
Rather than become just another smart manufacturing application focusing on machines, OptimalPlus brings its focus to the product being manufactured. Given NI’s strength in test and measurement, this was a definite synergy. As I have written before here and here, this enterprise software addition to NI’s portfolio is just what the company needs to advance a level.
Michael told me he was an early advocate for OMP due to seeing how his technology worked with Tier 1 automotive suppliers to drive digital transformation process.
NI announced that its latest acquisition, OptimalPlus, has joined the Open Manufacturing Platform (OMP), a consortium led by BMW, Microsoft, ZF, Bosch and ABInBev that helps manufacturers leverage advanced technologies to gain greater operational efficiencies, factory output, customer loyalty, and net profits.
The OMP’s goals include creating a “Manufacturing Reference Architecture” for platform-agnostic, cloud-based data collection, management, analytics and other applications. This framework will provide a standard way to connect to IoT devices on equipment and define a semantic layer that unifies data across disparate data sources. All in all, this has the potential to create a rich, open-source ecosystem that enables faster and easier adoption of smart manufacturing technologies.
In the same way that interpreters at the United Nations help delegates communicate and make new policies, standardized data formats accelerate the adoption of big data and machine learning, creating a universal translator between multiple machine and process types. OptimalPlus, now part of NI, will bring to OMP its vast domain expertise in automotive manufacturing processes and provide leading production companies with actionable insights and adaptive methods from its big data analytics platform.
“We’re honored to be invited to join the prestigious Open Manufacturing Platform, which plays a key role in helping manufacturers all over the world innovate,” said Uzi Baruch, VP of NI’s Transportation business unit. “With pressure mounting to ensure quality and prevent faulty parts from shipping, it’s important that manufacturers have access to the transformative powers of AI, machine learning and big data analytics. We’re excited to collaborate with industry leaders in the OMP consortium to help manufacturers evolve and optimize their processes.”
AI and advanced analytics help to streamline manufacturing, reduce costs and improve quality, reliability and safety. OMP makes it easier for manufacturers to deploy this technology across their operations and fulfill the promise of smart manufacturing.
White Paper: Insights Into Connecting Industrial IoT Assets
The second bit of news describes a first deliverable from the OMP as it progresses toward its objective.
OMP announced delivery of a critical milestone with the publication of our first white paper. The IoT Connectivity Working Group, chaired by Sebastian Buckel and co-chaired by Dr. Veit Hammerstingl of the BMW Group, authored Insights Into Connecting Industrial IoT Assets. Contributions from member companies Capgemini, Cognizant, Microsoft, Red Hat, and ZF present a consensus view of the connectivity challenges and best practices in IIoT as the 4th industrial revolution unfolds. This paper is the initial publication laying out an approach to solving connectivity challenges while providing a roadmap for future OMP work.
Manufacturing at an Inflection Point
The intersection of information technology (IT) and operational technologies (OT), as well as the advent of the Internet of Things (IoT), presents opportunities and threats to the entire manufacturing sector. In manufacturing, multiple challenges complicate the connection of sensors, actuators, and machines to a central data center. Lack of common standards and proprietary interfaces leads each engineer to solve similar problems, introducing inefficiencies and forcing the same learning curve’s ascension over and over. The long renewal cycles of shop floor equipment, software, and processes present gaps in modern technologies and a general avoidance of making significant institutional changes. This initial publication begins to tackle these problems and lays the groundwork for future, more detailed work.
Each connectivity challenge will have a range of diverse constituents and the content of this paper addresses issues faced by individuals and teams across job functions. Operational technology (OT) professionals are responsible for the commissioning, operation, and maintenance of shop floor equipment. Information technology (IT) personnel look after overall data processing, the hardware and software infrastructure, and enterprise-wide IT strategy. General managers and logistics teams are typically aligned at a corporate level, coordinating processes across a network of plants. Each of these functions will have roles spanning from operational hands-on to strategic and managerial. The unique demands of each part will require connectivity solutions to be forward-thinking and value-accretive while offering practical solutions implemented with minimal incremental investment.
Industrial IoT Challenges
Also explored in the paper, are the IIoT devices’ critical real-time needs for repeatability and high availability. An example is an AI model that optimizes the parameters of a bending machine based on the current air temperature and humidity. Possible connection failures or high latencies can lead to stopped or interrupted processes or products with insufficient quality.
Manufacturing throughput requirements vary from low bandwidth for simple sensors using small packets to much higher bandwidth required for streaming data for video analytics, vibration sensors, or AR/VR visualization. A holistic connectivity solution can address this complexity successfully, spanning from the individual devices on the shop floor up through edge gateways and servers to the central data center or cloud resources such as compute and storage.
Networks are usually customized to their precise environment and the desired function, and therefore can be very complex.
In the white paper, we discuss the functions of each of the network levels, their benefits and limitations, and security considerations. Additional sections of the document cover common challenges in IIoT, connectivity levels, basic principles for successful connectivity solutions, communication types, and best practices for program implementation.