Industrial DataOps Solution for Smart Manufacturing

HighByte expands edge-to-cloud connectivity, provides scalable data infrastructure for customers with latest release of HighByte Intelligence Hub 

DataOps is the current cool thing in the IT world. My last trip to an IT conference included an extended stay at the stand where it was discussing its DataOps solution. IT usage sometimes lacks specific connectors for specifically industrial use cases. The field was open for a company to come along in the “Industrial DataOps” market. And here is HighByte—a company composed of former Kepware industry veterans. I waited until I could view the demo before commenting. I like what I see. What’s the biggest challenge for digital transformation after we’ve learned how to control and visualize industrial processes along with building out IT infrastructure? That would be moving data along to the right place. Check out DataOps. You can view the demo of the latest version of HighByte’s product here.

HighByte has announced the release of HighByte Intelligence Hub version 1.3. The latest release provides simple, configurable connections to IT systems through direct SQL and REST integrations and native connectivity to Microsoft Azure IoT Hub, Microsoft Azure Event Hubs, and AWS IoT SiteWise. These new connections make it faster and easier for manufacturers to merge industrial data with enterprise systems and deliver ready-to-use information to the Cloud.

“While our customers span a variety of industries from biotechnology to packaging to industrial products, they all recognize that data infrastructure is foundational to their digital transformation initiatives,” said HighByte CEO Tony Paine. “The new connections in HighByte Intelligence Hub enable operations technology (OT) to curate, merge, and model production data with enterprise systems data and deliver it to the Cloud in real time. We’re providing a solution capable of bridging the data divide between OT and IT applications.” 

HighByte Intelligence Hub is an Industrial DataOps application designed to run at the Edge. The latest release adds additional edge-focused capabilities by supporting deployment in Docker and other containers and increasing data reliability through Store and Forward. The release also makes it easier for users to manage high volumes of data and work with complex data. The new drag and drop reference browser simplifies the user experience and accelerates deployment.  

AVEVA achieves Microsoft Gold Application Development Competency

Microsoft has positioned itself as a premier platform provider for manufacturing applications for a long time. It lists as partners just about every industrial/manufacturing application developer. Recently, AVEVA announced it has reached a new level of competency within the Microsoft ecosystem.

AVEVA has attained a Gold Application Development competency and Silver Cloud Platform, Data Analytics, and Data Center competencies, demonstrating a ‘best-in-class’ ability and commitment to meet Microsoft customers’ evolving needs in today’s mobile-first, cloud-first world and distinguishing itself within a small percentage of the Microsoft partner ecosystem. A portfolio of competencies showcases that AVEVA is committed to focusing on on-demand, business solution areas, along with ensuring it can meet the evolving needs of our mutual customers.

To earn a Microsoft competency, partners must successfully complete exams (resulting in Microsoft Certified Professionals) to prove their level of technology expertise and, for Gold competencies, designate these certified professionals uniquely to one Microsoft competency, ensuring a certain level of staffing capacity. Partners must also submit customer references that demonstrate successful projects and pass technology and/or sales assessments. For gold competencies, partners must also implement a yearly customer satisfaction study and, for many competencies, meet a revenue commitment.

“AVEVA is enabling industrial organizations to embrace innovative digital platforms that will allow them to deploy faster, reduce energy consumption and emissions, and work more collaboratively,” commented Steen Lomholt-Thomsen, Chief Revenue Officer at AVEVA. “These Microsoft competencies not only showcase our technology expertise, but also demonstrate our commitment to supporting customers and embracing innovation. By deploying our solutions, customers can be empowered to deliver better business outcomes, which will in turn help to accelerate their own success.”

“By accomplishing a portfolio of competencies, partners demonstrate true commitment to meeting customer technology needs today and into the future,” said Gavriella Schuster, corporate vice president, Worldwide Partner Group at Microsoft Corp. “These partners’ proficiency and expertise of Microsoft technology is instrumental in helping our mutual customers continue to drive innovative solutions.”

All 17 Microsoft technology competencies differentiate a partner’s specific technology capabilities, helping customers find qualified solution providers with expertise in discrete areas quickly and easily.

Earning the Application Development competency helps partners differentiate themselves as a trusted expert to their customers through development and deployment of commercial or custom applications built using core Microsoft technologies like Windows Server and Windows 8 operating systems, the Windows Azure platform, Microsoft Visual Studio 2012 development system, Microsoft BizTalk Server and emerging cloud-based and web business models. By gaining access to a comprehensive set of benefits through the Application Development competency, partners can acquire new customers and help them be more productive and profitable through deployment of business applications, advanced web portals or rich client user interfaces that run on premises or in the cloud.

The Cloud Platform competency is designed for partners to capitalize on the growing demand for infrastructure and software as a service (SaaS) solutions built on Microsoft Azure. Differentiate your company with the Cloud Platform competency, and you will be eligible for Signature Cloud Support, Azure deployment planning services, Azure sponsored credit, direct partner support, eligibility to deploy certain on-premises, internal use software on Microsoft Azure, and access to the cloud platform roadmap.

The Data Analytics competency recognizes partners who demonstrate expertise in specific aspects of Microsoft BI solutions to deliver, deploy, and support BI projects. Differentiate your company with this competency and receive access to internal use software licenses, technical and presales support, training for your IT professionals, developers, incentives, and marketing through the Partner Marketing Center and Pinpoint. Strengthen relationships with your customers by becoming a provider of SQL Server deployment planning services or SharePoint deployment planning services.

The Datacenter competency recognizes partners who are transforming data centers into more flexible, scalable, and cost-effective solutions. Partners can deepen customer relationships by becoming a provider of Private Cloud, Management, and Virtualization Deployment Planning Services. Differentiate your company with this competency and receive access to internal use software licenses, technical and presales support, training for your IT professionals, incentives, and access to the Microsoft Partner server and cloud site with exclusive content and resources to help you win new deals to deliver projects successfully.

The Microsoft Partner Network helps partners strengthen their capabilities to showcase leadership in the marketplace on the latest technology, to better serve customers and to easily connect with one of the most active, diverse networks in the world.

COVID-19 Reshapes Manufacturing Landscape, New Google Cloud Findings Show

This information came to me about a month ago. I’m still catching up with filtering through all the releases from the last couple of months last year. Covid may have kept many people indoors, but it didn’t slow down work in engineering, marketing, or PR. This is a survey conducted by Google Cloud and the Harris Poll regarding the effects of Covid on manufacturing. This is a blog post from Google’s Dominik Wee, Managing Director Manufacturing and Industrial.

After facing severe headwinds from COVID-19, ranging from decreased orders to negative impacts on operations, manufacturers around the world have started to revamp their operating models and supply chain strategies—and now feel more prepared to successfully navigate future pandemics, according to our new research released today.

The key for manufacturers’ ability to transform—despite the ongoing pandemic—is their embrace of digital enablers and disruptive technologies. In fact, more than two in five manufacturers have increased their use of data and analytics, digital productivity tools, and public cloud platforms, irrespective of their location in the world.

“Manufacturers have always prepared for unpredictable events that could adversely impact operations,” said Bob Parker, Senior Vice President, Enterprise Applications, Data Intelligence, Services, and Industry Research for IDC. “But what makes COVID-19 so unique is its sustained nature that touches the supply chain, irrespective of geographical location, in a way we haven’t seen in our lifetime. As a result, we’re seeing an urgency from manufacturers to quickly put the right technological levers in place, sooner rather than later. While there may have only been initial conversations about digital transformation in the past, we’re now seeing a rapid acceleration of critical tools and technologies being adopted within the industry.”

Below are five noteworthy takeaways we’ve identified within our findings:

1. Not surprisingly, as with other industries, the pandemic has had a devastating effect on manufacturers overall. Nearly all of manufacturers (95%) believe their manufacturing or supply chain operations have been negatively impacted by the pandemic. The top three adverse impacts include lost productivity (46%), lower sales (44%), and increased lead times, possibly due to supply chain disruptions (39%). About a third of manufacturers have also experienced downward pressure on overall customer demand (35%), labor shortages (34%), and/or the inability to maintain a safe working environment (33%).

2. To overcome COVID-19-related challenges, manufacturers were forced to pivot their operating models and supply chain strategies. More than three-fourths of surveyed manufacturers (77%) said COVID-19 caused their companies to re-evaluate their operating model strategies. The most common reasons include an inability to collaborate effectively with value chain partners (41%), the inability to collaborate effectively with employees (40%), and a lack of the right technology to operate without a large number of on-site workers (39%).

3. Technology played the most critical role in maneuvering through the pandemic, particularly “disruptive” AI, robotics, and more. More than three-fourths of surveyed manufacturers (76%) revealed that the pandemic has caused their companies to increase the use of digital enablers and disruptive technologies such as: cloud, artificial intelligence (AI), data analytics, robotics, 3D printing/additive manufacturing, Internet of Things, and augmented or virtual reality. More specifically, the top three digital enablers/disruptive technologies that respondents are further utilizing are data and analytics (46%), digital productivity tools (43%), and public cloud platforms (42%).

4. Interestingly, despite many manufacturers not being prepared for COVID-19, most now feel prepared to successfully navigate future pandemics. As mentioned earlier, nearly (95%) believe their manufacturing or supply chain operations have been negatively impacted by the pandemic. That said, 82% of those surveyed now feel prepared to deal with another COVID-19-like event in the future. This sentiment could be related to how manufacturers successfully ventured into new verticals, such as providing ventilators and PPE during shortages and resuming investments in new digital factory plans.

5. Finally, the pandemic—and its aftermath on the manufacturing industry—has differed greatly by country.

1. In Japan, approximately half of manufacturers who cited a negative impact (51%) say that the pandemic has led to lower sales, compared to 44% globally.

2. In Korea, more than two in five manufacturers who cited a negative impact (43%) said that the pandemic hindered their ability to maintain a safe working environment, compared to 33% globally.

3. In France, nearly half of manufacturers (48%) felt equipped with the right technological tools to maintain business continuity in the first 1-3 months of the pandemic, compared to 37% globally.

4. In the UK, more than two in five manufacturers (43%) said that dependency on legacy technology has created more risk for their respective business operations over the next year, compared to 30% globally.

5. In Italy, more than a third of manufacturers (35%) felt that their IT systems lacked necessary redundancies, which undermined their overall operational resiliency, compared to slightly less than a quarter of overall surveyed manufacturers (23%).

6. In Germany, for 86% of manufacturers, COVID-19 has caused an increased use of digital enablers and disruptive technologies, compared to 76% globally.

7. In the United States, 64%of manufacturers have increased their use of data and analytics, compared to 46% globally.

Research Methodology

The survey was conducted online by The Harris Poll on behalf of Google Cloud, from October 15 – November 4, 2020, among 1,154 senior manufacturing executives in France (n=150), Germany (n=200), Italy (n=154), Japan (n=150), South Korea (n=150), the UK (n=150), and the U.S. (n=200) who are employed full-time at a company with more than 500 employees, and who work in the manufacturing industry with a title of director level or higher. The data in each country were weighted by number of employees to bring them into line with actual company size proportions in the population. A global post-weight was applied to ensure equal weight of each country in the global total.

Intelligent Agents as a booster for European production

  • Artificial Intelligence coordinates multi-agent systems
  • Implementing European projects on the demonstrator in Kaiserslautern

The Chief Technology Officer of a major automation supplier once told me that an important technology I should keep an eye on was intelligent agents. Indeed, the poor little software object rarely gets star billing on the program. The technology does exist. This information came to me last month about multi-agent systems. It encompasses a European smart factory initiative. This initiative bears watching.

A consortium of seventeen European partners is developing multi-agent systems for autonomous modular production in the research project called MAS4AI (Multi-Agent Systems for pervasive Artificial Intelligence to assist humans in modular production environments). The European Union (EU) has funded the project with almost 6 million euros.

MAS4AI is a project focused on selected sectors of industry that plans for their smart digital transformation over the next three years using the tools of Artificial Intelligence (AI). The aim is to achieve resilient production that can react flexibly to changing requirements or disruptions in the added value networks. The underlying basis is the large variety of products in lot size 1 in complex manufacturing operations.

Single agents acting in concert
Multi-agent systems are an area of distributed artificial intelligence research, in which several differently specialized “intelligent” and mostly autonomous software components (agents or bots) act in a coordinated manner to jointly solve a problem. The researchers are working towards the long-term goal of stable production, which among other things, relies on Shared Production and Production-as-a-Service. Communication, synchronization, and coordination of skills (production capabilities) are needed in a production network in order to implement our vision. This coordination will be performed by AI processes in the future. The European project partners envision a future production that can be distributed in European networks (like GAIA-X).



People make the decisions​​​​​​​
Scientists and engineers from Greece, Germany, Italy, Lithuania, the Netherlands, Poland and Spain are initially working on a modular system architecture and a communication structure to create the foundation on which to integrate industrial AI services for smart production. In the process, human participants will always retain control over the AI technologies. The prerequisite for this is to have AI processes designed in a way that is always understandable to the operator. Only then can they be validated, optimized, or modified. Demonstrators oriented on a series of industrial use cases are being developed in MAS4AI. The use cases are in European industrial sectors of high added value, such as companies from the automotive industry, contract manufacturing, bicycle production, or wood processing.

Production Level 4 as the visionary basis​​​​​​​
“MAS4AI fits perfectly into our concept of Production Level 4, which is based on production-bots and modular networks. Our concept envisions future production resources that offer their capabilities (skills) to the networks and autonomously (self-directed) call up the products,” said Prof. Martin Ruskowski, Chairman of the Executive Board of SmartFactory-KL, Head of DFKI’s Innovative Factory Systems research, and Chair of the department of Machine Tools and Controls at TU Kaiserslautern. “The products in our vision know their attributes and their current production progress. Such products search their own way among the skills to complete their own production. This may take place in a facility, but also in a Europe-wide network.”

Four scientific and technological goals

The consortium is developing the following four topics:

  1. Multi-agent systems for the distribution of AI components at various levels of a hierarchy. The key idea is to control interaction between agents on a task-specific basis with agents integrated to form an overall system.
  2. AI agents that use knowledge-based representations with semantic web technologies. Every agent can detect what skills it has to offer and those of other agents and, in this way, decide what action should be executed. This also makes it easier to integrate people into the production, because the data is also prepared in a way that is understandable to them.
  3. AI agents for the hierarchical planning of production processes. Processes are broken down into individual steps and optimally reassembled according to the current requirements. Disturbances in the flow can be compensated.
  4. Model-based AI agents for Machine Learning (ML). These hybrid models are designed to combine human knowledge about physical processes with data acquired for machines.

A fundamental concept in MAS4AI is the integration of all smart components (machines with attributes like self-direction, self-description, and self-learning abilities) in a holistic system architecture. This facilitates easy development and use of industrial AI technologies. Software developers, system integrators, and end users will all benefit because the hurdle for the use of AI is low. “We expect this to generate revolutionary ideas for business models as well as brand new market opportunities,” said Ruskowski.

Partners:

  • Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, Deutschland
  • Nederlandse Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek, Niederlande
  • University of Patras – Laboratory for Manufacturing Systems & Automation, Griechenland
  • Fundacion Tecnalia Research and Innovation, Spanien
  • Asociacion De Investigacion Metalurgica del Noroeste, Spanien
  • University of Silesia, Polen
  • Volkswagen AG, Deutschland
  • SCM Group Spa, Italien
  • SC Baltik Vairas, Litauen
  • VDL Industrial Modules, Niederlande
  • Fersa Bearings S.A., Spanien
  • Semaku B.V., Niederlande
  • Symvouloi Kai Proionta Logismikou, Griechenland
  • flexis AG, Deutschland
  • Sisteplant, S. L., Spanien
  • D.M.D. Computers SRL, Italien
  • Smart Manufacturing Competences Centre INTECHCENTRAS, Litauen

TwinCAT IoT Now Supports MindSphere

Beckhoff integrates data and communication services efficiently into the cloud with support for third-party IoT technologies

Where these IIoT platforms/ecosystems end up is beyond my power to guess, but this is an interesting partnership of a couple of German control and automation rivals—Beckhoff Automation and Siemens.

Beckhoff has offered diverse IoT communication capabilities with its TwinCAT IoT product family since 2015. Transmitting data to the cloud or between networked machines in this way creates enormous potential for increasing production efficiency. MindSphere, the Industrial IoT as a service solution from Siemens, is now one of the latest solutions that can integrate with TwinCAT.

TwinCAT 3 automation software can communicate with HTTP(S) servers as an HTTP(S) client, for example for exchanging data via a REST API. Establishing a connection with MindSphere is now also possible via this HTTPS communication for exchanging telemetry data. This connection is secured by TLS (Transport Layer Security) and uses MindSphere-specific authentication mechanisms.

The sample implementations of the TwinCAT 3 Function TC3 IoT HTTPS/REST (TF6760) in the relevant documentation show how to establish connections with MindSphere. These examples provide a simple introduction to connecting TwinCAT with MindSphere and help users to adapt the program code to suit individual requirements.