The results of a recent survey. Where do you fit on their maturity index? Hopefully you are using the technologies and obtaining positive results.
Analog Devices, Inc. announced a newly commissioned study conducted by Forrester Consulting on behalf of Analog Devices, that shows that industrial manufacturers who have made investments in connectivity technologies (“high maturity”) are better positioned to drive innovation and gain a competitive advantage compared to firms that have been slower to implement connectivity (“low maturity”) across the factory floor.
The study, based on a survey of more than 300 manufacturing, operations, and connectivity executives across the globe, found that 85% of high maturity firms are currently using Industrial Internet of Things (IIoT) technologies across much of the factory floor, compared to 17% of low maturity organizations. Over half (53%) of low maturity organizations report that their legacy equipment is unable to communicate with other assets.
“This past year was a true catalyst for digital transformation and many businesses needed to navigate and adopt connectivity strategies that helped them to become more agile and lay the groundwork for future innovation,” said Martin Cotter, SVP Industrial, Consumer & Multi-Markets at Analog Devices. “We see significant opportunity in the adoption of connectivity solutions, including 5G, to help organizations get data more quickly, enabling end applications.”
Findings from the research include:
- Connected firms believe that improving network reliability (including adding 5G networks) will create significant opportunity: 68% of high maturity firms say this will enable them to make better use of existing cloud infrastructure and 66% believe their industrial data and IP will be more secure. Conversely, only 21% of low maturity firms believe that improving network reliability will help improve security. However, all respondents agree that improving network reliability will improve efficiency by freeing up employees who are constantly resolving downtime issues.
- Low maturity firms struggle with security risk: 54% say that their lack of sophisticated cybersecurity strategy puts their business, customer, and employee safety at risk.
- The human element continues to pose challenges: Almost half (47%) of low maturity firms say they lack the expertise to understand which connectivity technologies to invest in, indicating a skills gap. Even high maturity firms report that it is not easy for them to access the insights they need to make labor planning and safety decisions.
- Real-time monitoring of equipment and productivity demonstrates an acute awareness of the high cost of unscheduled downtime: High (5%) and medium (17%) maturity firms reported much lower occurrence of unscheduled downtime of their industrial technology or equipment each week than low maturity companies (53%). These interruptions, lead to higher cost of holding inventory and labor per unit, loss of production and customer confidence and decreased work capacity.
This research shows us that while many firms are benefiting from the promise of industrial connectivity, others have significant legacy and talent-related hurdles to overcome. Innovation is hindered by both a shortage of in-house expertise and interoperability of systems and data, two major hindrances to manufacturing modernization.
Methodology: For this study, “Seamless Connectivity Fuels Industrial Innovation” (March 2021) – commissioned by Analog Devices – Forrester Consulting conducted a global online survey of 312 industrial connectivity strategy leaders. Survey participants included decision-makers in IT, operations, cybersecurity, and general management manufacturing roles. The study was conducted in October 2020.
For the full study click here.
ZEDEDA has been in the news here before. I also participated in a day-long conference with the company and many guests. The company has been making a splash with open-source and edge orchestration. Funding news, while exciting to the company, is not always that interesting to me. What I find intriguing here is that one of the investors is Rockwell Automation. That company has been making some forays outside its longtime control business. This will be fun to watch.
- Oversubscribed round includes new strategic investors Rockwell Automation, Juniper Networks and EDF North America Ventures, along with existing investors Almaz Capital, Energize Ventures, Lux Capital and HBAM
- New capital will accelerate investments in R&D, sales, and marketing
- ZEDEDA expects to more than triple the number of customer edge nodes under management by mid-2021
ZEDEDA announced a $12.5 million highly oversubscribed expansion to its $16 million Series A round initially closed in February 2019, bringing its total funding to-date to $28.5 million.
The latest round of institutional funding validates the traction ZEDEDA has achieved across the market as customers adopt its disruptive orchestration solution for the distributed edge. ZEDEDA will use the new influx of capital to continue to scale its operations, including investments in R&D, sales and marketing.
New strategic investors Rockwell Automation, Juniper Networks and EDF North America Ventures (a wholly owned subsidiary of EDF Trading North America) recognize the market opportunity of edge computing and ZEDEDA’s opportunity as the first in the industry to solve the unique challenges of deploying, managing and securing hardware and applications at the distributed edge on-premises, near-premises and in the field. Existing investors participating in the round included Almaz Capital, Energize Ventures, Lux Capital and HBAM.
Operationalizing Secure Distributed Edge Computing at Scale
With the edge computing market expected to more than quadruple over the next four years, enterprises realize that their strategic vision must implement an open foundation that enables visibility, control and security for their edge projects at scale. Companies can achieve those strategic imperatives only by leveraging an as-a-service model, which takes advantage of a recurring software subscription and enables enterprises with a cloud-native architecture at the edge that scales on demand while supporting legacy investments.
ZEDEDA’s cloud-based orchestration solution, sold and consumed itself entirely as-a-service, enables complete flexibility for end users, OEMs, machine builders, technology providers and system integrators, with support for any hardware, any application and any cloud or on-premises system. The company expects to more than triple the number of customer edge nodes under management by mid-2021 from today.
“Our new strategic investors, as well as the existing investors who joined in again, bring years of experience in our core industries of manufacturing, oil and gas, energy, telco and retail,” said ZEDEDA founder and CEO Said Ouissal. “Their investment is a validation of our progress, but it also means we have the opportunity to meet the needs of any company who needs to orchestrate applications and hardware outside of traditional data centers.”
Investor Perspectives on $12.5M Strategic Institutional Funding Round
“We see investment in software development to be a key opportunity for driving future growth, including accelerating our Software-as-a-Service opportunities,” said Brian Shepherd, Senior Vice President, Software & Control at Rockwell Automation. “With its focus on providing a flexible edge architecture that meets the needs of existing industrial customers while providing them a path to modernization, as well as enabling new customers seeking to leverage more agile, cloud-native technologies, ZEDEDA’s as-a-service solution fits naturally into our overall strategy.”
“With our commitment to building a net-zero energy future, we believe it’s critical to enable energy providers to optimize operations, maximizing efficiency and output,” said Mary Ann Brelinksky, President, EDF Energy North America. “IoT and edge computing are instrumental in driving these efforts, and ZEDEDA provides the perfect computing foundation that will scale for the future, enabling our customers to implement new technologies that will analyze and respond in real time to their operations.”
“At Juniper, we see the AI-driven enterprise as an important strategic opportunity in the market to enable businesses to extract and utilize previously unrecognized value from existing and new sources of data,” said Kevin Hutchins, Senior Vice President, Strategy and Business Development, Juniper Networks. “ZEDEDA operationalizes distributed edge computing, making it possible to implement and manage the entire process, from hardware to applications, in a secure and scalable manner.”
“As one of ZEDEDA’s early investors, we have been excited to see the company’s execution of its vision,” said Geoffrey Baehr, General Partner, Almaz Capital. “The market size of the edge computing market, combined with ZEDEDA’s ability to realize its vision into a generally available solution of strategic importance to its Fortune 500 companies, makes this the right time to significantly increase our investment in the company.”
Many people remain confused about just what an Internet of Things (IoT) project consists of. Various analysts predict astronomical numbers for potential connected things. We know that a large industrial facility could have thousands, or indeed hundreds of thousands, of sensors and other data points. Testing the performance and resilience of such a network can be both daunting and critical. HiveMQ claims a solution with a platform built upon MQTT.
HiveMQ Swarm Complements HiveMQ MQTT Platform to Deliver a Complete Solution for Enterprises Deploying Large-Scale IoT Solutions
HiveMQ announced HiveMQ Swarm, the industry’s first solution that enables organizations of all sizes to reliably simulate and test large-scale IoT networks. HiveMQ Swam enables enterprises to easily test the scalability and performance of their IoT deployments, resulting in significantly increased quality and reliability of their system. HiveMQ Swarm is also the first solution that provides global enterprises with a superior solution to forecast capacity, infrastructure, and financial cost planning prior to putting their IoT system into production.
“As IoT solutions continue to grow in both scope and volume, the ability to test IoT solutions for scale and performance becomes mission-critical,” said Dominik Obermaier, CTO and founder of HiveMQ. “We have extensive experience with some of the largest IoT systems in the world. These customers have asked us to help them validate their systems before going into production. Swarm meets these needs by enabling our enterprise customers to ensure their large-scale IoT systems perform to expectation the first time they’re deployed.”
IoT systems are incredibly difficult to test prior to production. Emulating behavior in a production environment is often unreliable and individual IoT devices can demonstrate multiple complex behavior patterns. For example, autonomous vehicles at rest behave very differently than those navigating the unexpected events they encounter in the real world, be it a highway or a factory floor.
Despite these challenges, load and stress testing is an unavoidable reality, as fixing IoT production errors in the field can be incredibly expensive, not to mention that these errors can have potentially catastrophic results on the system itself. As a result, determining system resilience is a mission critical endeavor.
HiveMQ Swarm was designed specifically to solve these challenges. Swarm is a distributed platform able to create hundreds of millions of unique network connections that simulate devices, messages, and MQTT topics (a form of addressing that allows MQTT clients to share information), as well as develop reusable scenarios that emulate device behaviors. In addition to a custom data generator to create complex use cases for testing, HiveMQ Swarm is designed to seamlessly integrate with enterprise cloud infrastructure, including public clouds (e.g., AWS, Azure, GCP) and Kubernetes-based systems.
HiveMQ Swarm is complementary to the HiveMQ MQTT platform, an MQTT broker messaging platform designed for the fast, efficient and reliable movement of data to and from connected IoT devices. It uses the MQTT protocol for instant, bi-directional push of data between devices and enterprise systems.
Another example of industrial technology companies working with Microsoft Azure. The Cloud race is heated.
IOTech, the edge software company, announced the launch and availability of Edge XRT, its time-critical edge platform for Microsoft Azure Sphere. Designed and optimized for resource-constrained environments, Edge XRT delivers out-of-the-box device connectivity and edge intelligence for microcontroller units (MCUs), gateways and smart sensors at the IoT edge. It reduces time-to-value from weeks to hours.
Azure Sphere is a secured, high-level application platform with built-in communication and security features for the connected devices. It comprises a connected crossover microcontroller unit, a custom Linux-based operating system, and a cloud-based security service.
“We’re delighted to collaborate with Microsoft and its partners to deliver real-time IoT edge capability for low-profile, yet powerful, devices,” said Keith Steele, CEO of IOTech. “The availability of Edge XRT for use with Microsoft Azure Sphere is an important step to accelerate the deployment, and even more importantly, dramatically reduce the time-to-value, for both greenfield and brownfield IoT edge solutions.”
Edge XRT for Azure is fully compatible with Azure Sphere-certified chips and Azure Sphere OS. An Azure Sphere device is designed to integrate securely with the Azure Sphere security service running in the cloud. The security service ensures the integrity of the device and provides the secure channel used by Microsoft to automatically install Azure Sphere OS and customer application updates to deployed devices.
Edge XRT reduces the time-to-value for Azure Sphere, delivering securely connected device service deployments from weeks to hours. In addition, by moving specific workloads to the edge of the network, devices spend less time communicating with the cloud. The result is devices react more quickly to local changes and operate reliably, even in extended offline periods.
Edge XRT simplifies connectivity to sensors and devices at the edge by configuration versus coding. This enables connectivity to Azure Sphere devices using a range of standard industrial protocols such as Modbus, BACnet, EtherNet/IP and others. It allows ready access to edge data, which can be sent securely to and from its digital twin running on Azure IoT Hub.
Edge XRT can also host edge intelligence applications for Azure Sphere devices. It allows users to create edge applications that can be downloaded and updated securely over the air via the Azure Sphere security service throughout the life cycle of the device.
“Microsoft is pleased to collaborate with IOTech to enable the integration of device data with Microsoft Azure Sphere deployments,” said Galen Hunt, Distinguished Engineer and Managing Director of Azure Sphere, Microsoft. “Edge XRT software helps reduce device integration configuration time and deployment, helping customers and partners realize value from IoT solutions rapidly and at scale.”
Here are announcements from the Industrial Internet Consortium (IIC) regarding two white papers released. One deals with IioT Models and the other with innovation processes of digital transformation. A lot of thinking went into these.
The Industrial Internet Consortium (IIC) announced the publication of the Characteristics of IIoT Models White Paper. Interoperability between applications, subsystems, and devices in Industrial Internet of Things (IIoT) systems requires agreement on the context and meaning of the data being exchanged, or semantic interoperability, which is typically captured in an information model. The new white paper addresses the challenge of integrating subsystems in IIoT systems that use different information models and examines how standardized information models that use a descriptive or semantic approach enable interoperability and ultimately digital transformation.
The variety of digital data and information systems is an indispensable attribute of the modern world of IIoT. In each industrial vertical, one way or another, work is underway to reach agreements between stakeholders through the development of standards and data schemas. Our white paper provides a simple definition of the characteristics and properties of information models, which can be useful in the design of IIoT systems and, which is especially important, for multiple systems to work seamlessly with each other.
“Semantically based information models can share data across domain boundaries using a descriptive approach (instead of a translational approach) as the data has meaning in both domains, and the full fidelity of the original data are maintained,” said Kym Watson, Co-chair of the IIC Distributed Data Interoperability and Management Task Group, an author of the white paper and Scientist at Fraunhofer IOSB. “Our intent in this white paper is to survey a subset of information models that are relevant to the IIoT and characterize those information models using a meta-model developed for this purpose. With this we capture commonalities and can begin to address the challenge of integrating subsystems that use different information models.”
“An information model is a representation of concepts, relationships, constraints, rules, and operations to specify data structures and semantics,” said Niklas Widell, Co-chair of the IIC Distributed Data Interoperability and Management Task Group, an author of the white paper and a Standardization Manager at Ericsson. “There are multitudes of information models available or under active development for a variety of application domains or industries. We focused on information models above the Industrial Internet of Things Connectivity Framework layer where semantic interoperability, including translation between different models, plays a key role.”
The white paper examines the following standardized information models (among others) that are widely applied in IIoT applications:
• Web of Things – a set of standards by the W3C for solving the interoperability issues of different IoT platforms and application domains.
• SensorThings API – an Open Geospatial Consortium standard providing an open and unified framework to interconnect IoT sensing devices, data, and applications over the Web.
• OPC UA – a machine-to-machine communication protocol for industrial automation developed by the OPC Foundation focusing on communicating with industrial equipment and systems for data collection and control.
• Asset Administration Shell – a key concept of Industry 4.0 used to describe an asset electronically in a standardized manner. Its purpose is to exchange asset-related data among industrial assets and between assets and production orchestration systems or engineering tools.
• IPSO Smart Objects – a lightweight design pattern and object model to enable data interoperability between IoT devices, building on the LwM2M IoT device management standard, specified by OMA SpecWorks
• One Data Model/Semantic Definition Format – an initiative to improve interworking across different ecosystems’ data models using an emerging standard from the IETF. The OneDM Liaison Group adopts and aligns IoT models contributed by participating organizations, so best practice models for desired features or purposes can be identified.
“Standardized information models with defined semantics and APIs are an essential foundation for any form of digital transformation,” said Andrei Kolesnikov, Co-chair of the IIC Distributed Data Interoperability and Management Task Group, an author of the white paper, and director of the Internet of Things Association IOTAS. “There must be a seamless integration across the system life cycles, especially engineering and operations for all data sharing technologies.”
IIC members who wrote the Characteristics of IIoT Models White Paper and a list of members who contributed to it can be found here on the IIC website.
IIC White Paper Identifies Innovation Process For Digital Transformation
BizOps for digital transformation in industry facilitates IT and OT integration with better business outcomes
Industrial Internet Consortium (IIC) today announced the publication of the BizOps for Digital Transformation in Industries white paper. The new white paper identifies the BizOps for Digital Transformation in Industry (BDXI) innovation process, offering examples of a BDXI framework as crucial for IIoT solutions operators undergoing digital transformation.
“Digital transformation is a huge topic influencing almost every department of a firm,” said Co-author of the white paper Kai Hackbarth, Business Owner Industrial at Bosch.IO. “Solutions operators must integrate IT and OT to achieve better business outcomes, especially in asset-driven industries such as agriculture, energy, health care, manufacturing, retail, smart cities, and transportation. This is not an easy task as the process is slow and likely to conflict with existing processes and management systems.”
“The BDXI process is a fast, open, and customer-centric innovation process that considers the constraints and complexity of IT/OT integration and the physical world,” said Co-author of the white paper Chaisung Lim, Group Chair of the IIC BizOps for Digital Transformation in Industry Contributing Group, Chairman of the Korea Industry 4.0 Association, and a professor of Konkuk University. “A BDXI process helps IIoT solutions operators manage the innovation process from idea to launch successfully.”
A BDXI process includes discovering customer needs, developing solutions, learning whether solutions are feasible, and putting them into action. This necessitates dialogue between IT and OT stakeholders who would otherwise be constrained by organizational silos, a customer-centric process of checking solution validity, and fast experimentation with minimum viable products and agile methods. The most common features of BDXI processes includes the adoption of the best innovation practices from design thinking, lean start up and agile methods, and BizDevOps (the integration of IT/OT). BDXI process must be supported by a BDXI framework that offers a guide for implementing BDXI process concretely.
The BizOps for Digital Transformation in Industry white paper delves into the most common features of BDXI processes, examples of BDXI processes and frameworks, conflicts between BDXI processes and management systems, and IIC initiatives to help guide BDXI processes. IIC authors and contributors to the BizOps for Digital Transformation in Industry white paper can be found here on the IIC website.
What do you do when you want to bring the latest IoT, Digital Twin, data analysis to legacy equipment that is still producing in your plant? This announcement just came my way to answer the question. Getting past my particular hang-up on predictive maintenance, there are some really useful solutions in here.
Using advanced 3D Digital Twin, AI, and machine learning technology innovative platform and sensor solution provide real-time insights into legacy equipment for triage and issue resolution
UrsaLeo, an enterprise software company that enables users to visualize operational data in a photorealistic 3D representation of their facility or product, and Shiratech, a world-leading specialist in Industry 4.0-based condition monitoring and predictive maintenance technologies, announced a collaboration to offer advanced 3D Digital Twin, AI, sensor, and machine learning technology. The combination of the UrsaLeo platform with Shiratech’s iCOMOX solution integrated into legacy equipment allows manufacturers to plan, predict, and prevent performance issues.
“For many manufacturers, replacing legacy equipment can cost anywhere from hundreds of thousands to millions of dollars and may not be necessary with machinery that already operates at a high-performance level,” said John Burton, CEO of UrsaLeo. “Many types of older assembly equipment can be IIoT-enabled quickly, easily and cost-effectively, which is why the collaboration with Shiratech is vital to help bring companies with older equipment into the world of Industry 4.0.”
When I asked Burton how this happens, he told me, “We use a Shiratech sensor box that can be attached to the outside of an existing piece of machinery. It monitors, vibration, sound, magnetic field strength and current consumption. Once the ‘patterns’ the machine gives off are learned during normal operation, variations in those patterns can be detected by a human or by a machine learning algorithm. Not as good as having sensors inside equipment, but still good at detecting problems before failures happen.”
“The iCOMOX solution enables the precise monitoring of vibrations, magnetic-field, temperature, sound, and current. Using advanced AI and machine learning technology on edge this innovative solution provides real-time data about machine health, which is relayed directly to the cloud for analysis and real-time issue resolution,” said David Vactor, Managing Director of Shiratech.
Industrial machinery is designed to be a workhorse and can often last for many years before needing to be replaced. Without having to build an advanced factory or invest capital in new equipment, the UrsaLeo/Shiratech solution is ideal for cost-conscious executives looking to reap the benefits of Industry 4.0.