by Gary Mintchell | Sep 11, 2019 | Internet of Things, Manufacturing IT
Major IT companies have been scrambling to compete in the Industrial Internet of Things market. The control, instrumentation, and automation companies all talk about how this is all stuff they’ve been doing for years, or even decades, this is really quite new.
The first IT company people I talked with talked about selling boxes—gateways or edge computing. I’m thinking that there’s not enough money in that market. And, I was right. As the companies flesh out their strategies, the IoT group leadership keeps moving higher up the corporate ladder. And the vision broadens to include much of the portfolio of the companies enabling them to progressively enhance their competitive positions within their major customers.
Hitachi Vantara has recently been talking with me about their approach to the problem. I learned about Vantara and its focus initially through people I knew who landed new positions there. Life is always about serendipity. In the past, I’ve reported on the Lumada platform and the way the company is building modularly atop it. There was Maintenance Insights and then Video Insights. Now unveiled is Manufacturing Insights. I will get a deeper dive and talk to customers the second week of October when I attend its customer conference.
Note that these applications have more in common with MES than what you might think of as simply connecting devices with IIoT. In other words, the value proposition and integration into the customer grows.
Let’s discuss the latest addition to the Hitachi Lumada platform, Manufacturing Insights, which the company describes as a suite of industrial internet-of-things (IoT) solutions that empower the manufacturing industry to achieve transformative outcomes from data-driven insights. Using artificial intelligence (AI), machine learning (ML), and DataOps, Lumada Manufacturing Insights optimizes machine, production, and quality outcomes.
“Data and analytics have the power to modernize and transform manufacturing operations. But for too many manufacturers today, legacy infrastructure and disconnected software and processes slow innovation and impact competitive advantage,” said Brad Surak, chief product and strategy officer at Hitachi Vantara. “With Lumada Manufacturing Insights, customers can lay a foundation for digital innovation that works with the systems and software they have already to operationalize immediate gains in uptime, efficiency and quality and transform for the future.”
Accelerate Manufacturing Transformations
Lumada Manufacturing Insights applies data science rigor to drive continuous improvement opportunities based on predictive and prescriptive analytics. The solution integrates with existing applications and delivers actionable insights without the need for a rip-and-replace change of costly manufacturing equipment or applications. Lumada Manufacturing Insights supports a variety of deployment options and can run on-premises or in the cloud.
“With Hitachi Vantara, our customers benefit from our deep operational technology expertise and distinctive approach to co-creating with them to accelerate their digital journey,” said Bobby Soni, chief solutions and services officer at Hitachi Vantara. “With our proven methodologies and advanced tools, we can tailor solutions for our customers that enhance productivity, increase the speed of delivery, and ultimately deliver greater business outcomes.”
Providing machine, production and quality analytics, Lumada Manufacturing Insights drives transformational business outcomes by enabling customers to:
• Build on the intelligent manufacturing maturity model and empower the digital innovation foundation for continuous process improvement.
• Integrate data silos and stranded assets and augment data from video, lidar, and other advanced sensors to drive innovative new use cases for competitive advantage.
• Drive 4M (machine, man, material and methods) correlations for root-cause analysis at scale.
• Evaluate overall equipment effectiveness (OEE) and enhancement recommendations based on advanced AI and ML techniques.
• Evaluate scheduling efficiency and optimize for varying workloads, rates of production and workorder backlogs.
• Monitor and guide product quality with predictive and prescriptive insights.
• Improve precision of demand forecast and adherence to production plans and output.
Customer Comments
I hope to get more depth while I’m at the Next 2019 user conference Oct. 9-10. Here are some supplied quotes.
“Significant short-lead products have to be designed, prototyped and delivered to meet the demands of our customers and partners as we accelerate the product supply for 5G. Ericsson and Hitachi Vantara have collaborated to test Lumada Manufacturing Insights to gear up for an anticipated increase in new product introductions, establishing a digital innovation foundation for sustained gains,” said Shannon Lucas, head of customer unit emerging business for Ericsson North America. “We are leveraging the same solution that we will take to our joint customers in partnership with Hitachi Vantara, and will further expand IIoT use cases based on our 5G technologies.”
“As a progressive manufacturer, our focus was to accelerate transformative change, eliminate data silos and build a foundation for digital innovation that would accelerate our journey toward Manufacturing 4.0. “We leveraged the IIoT workshop to align our use cases with our business transformation priorities and have a roadmap for success with Lumada Manufacturing Insights,” said Vijay Kamineni, business transformation leader at Logan Aluminum. “The collaboration with Hitachi Vantara enables us to define business goals for each stage of our transformation, with clear outcomes that we believe will accelerate gains in productivity, quality, safety and sustainable manufacturing. “Hitachi Vantara brings a unique IT/OT advantage that will help us in the long run.”
“Humans and machines working together to deliver the vision of ‘digital drilling’ is driven by our ambition to achieve transformative outcomes, drilling our best wells every time and consistently achieving Target Zero for accidents. With Hitachi Vantara, we are realizing time to value with industrial analytics and the powerful Lumada platform to process more than 20,000 data streams per second per rig, providing actionable information to the right people at the right time and helping make optimal decisions. This drives our operational excellence and consequently our competitive advantage,” said Shuja Goraya, CTO at Precision Drilling Corporation. “We’re leveraging insights from video and lidar, integrating it with Lumada Manufacturing Insights to deliver business outcomes. It’s driving process optimization through effectively identifying improvement opportunities and shortening well delivery times for our customers. It’s all about effective use of data to make better decisions and then being able to consistently execute on these learnings. We are excited about our strategic partnership with Hitachi Vantara.”
Availability
Lumada Manufacturing Insights will be available worldwide Sept. 30, 2019.
by Gary Mintchell | Sep 10, 2019 | Internet of Things, Manufacturing IT
Sean Riley, Global Director of Manufacturing and Transportation at Software AG, discussed Industrial IoT (IIoT) implementation in industry with me a couple of weeks ago. Now, a survey sponsored by Software AG has been released revealing that manufacturers are not scaling IIoT across the enterprise due to failure to invest in predictive analytics and innovative integration strategies.
The shocking thing to me about the survey is that it mirrors survey results over the past three or four years. Executives and managers recognize a problem further even acknowledging that this is something that could cost them competitively against the market even putting them out of business. Yet, they cannot figure out how to do it right. They whine about how tough it is.
Sounds to me like a new crop of leadership is needed.
There are good practices taught some 40 years ago when I took a deep dive while implementing my first IT project. Things like understanding the system first. Bringing all the departments in on the plans, work to be done, and benefits we all would get. Some recommendations from Software AG sound that familiar—breaking silos, bringing IT and OT organizations closer together (a management problem, not a technical one), transparency in the project roll out.
The survey of over 125 North American manufacturers primarily in the heavy industry and automotive sectors revealed inability to scale IIoT investments across their enterprises results in losing millions of dollars in potential profits.
The survey also revealed that the vast majority of manufacturers queried report that their IIoT investments are limited – locked in one small department or sector of their company – preventing these organizations from sharing the power of IIoT across their enterprises.
Other key findings include:
- 80% of all survey respondents agree that processes around IIoT platforms need to be optimized or they will face a competitive disadvantage but very few are doing this
- IT-OT integration is considered one of the most difficult tasks – with 57% of automotive manufacturers stating that this has prevented them from realizing full ROI from their IIoT investments
- 84% of automotive and heavy industry manufacturers agree that the most important area of IIoT is “monetization of product-as-a-service-revenue.” However, optimizing production is still important with 58% of heavy industry and 50% of automotive manufacturers agreeing with that statement
- Curiously, defining threshold-based rules is considered almost as difficult as leveraging predictive analytics to scale IIoT. More than 60% of respondents stated that defining threshold-based rules was as difficult as integrating IT systems and IoT sensors into existing control systems.
“Manufacturers place a high value on IIoT, but they are encountering serious difficulties in unlocking the complete intended value to unleash their innovation across their organizations,” said Riley. “Fortunately, there is a way for them to quickly and easily resolve this problem. By investing in the right IT-OT integration strategy that leverages sensors, predictive analytics, machine learning, control applications, and product quality control, manufacturers can fix this problem in less than 6-12 months while realizing other key benefits, namely extended equipment lifetime, reduced equipment maintenance costs and accessing more accurate data for production-quality improvements.”
Riley outlined five best practices for manufacturers to follow when looking to scale their IIoT investments across their enterprises and realize immediate profits and competitive advantage. Those best practices are:
1. Ensure clear collaboration between IT and the business by leveraging a step by step approach that starts focused and has clear near term and long- term objectives to scale
2. Create a transparent roll out process and don’t let other plants or departments move ahead outside of it
3. Give IT the ability to connect at speed with a digital production platform that is proven to be successful
4. Leverage a GUI driven, consistent platform to enable an ecosystem of IT associates, business users and partners around the platform
5. Enable the plant or field service workers to work autonomously without continual support from IT through GUI driven analytics, centralized management and easy, batch device connectivity and management
Riley also stated that it is critically important for manufacturers to select the best possible IIoT integration platform supported by key enabling technologies like streaming analytics, machine learning, predictive analytics and a larger ecosystem. Software AG’s Cumulocity IoT platform recently received the highest use case scores from Gartner Group in the brand new “Critical Capabilities for Industrial IoT Platforms” report which included Monitoring Use Case, Predictive Analytics for Equipment Use and Connected Industrial Assets Use Case for its IoT.
The Software AG IIoT Implementation survey was completed in Q2 2019 by Software AG and an independent third-party research house. The survey queried nearly 200 respondents at large manufacturing companies across automotive, heavy industry, high-technology, electronics, pharmaceutical and medical device industries. The respondents were primarily senior executives leading Manufacturing or Information Technology with the breakdown of 50% Managers, 38% Directors and 13% Vice Presidents or higher.
Software AG product
The press release contained some information about the company’s IoT platform—Cumulocity.
Being device and protocol agnostic allows it to connect, manage, and control any “thing” over any network. Cumulocity IoT is open and independent, letting customers connect to millions of devices without being locked into one single vendor.
by Gary Mintchell | Aug 21, 2019 | Internet of Things
The Industrial Internet of Things by definition is all about connections. Connecting hundreds of devices which often have differing protocols is a huge challenge. In an attempt to facilitate IIoT deployments, ioTium has announced an alliance with Telit. The agreement allows Telit deviceWISE gateway technology on the ioTium Edge App Store for single-click deployment.
After wading through a couple of paragraphs of marketing generalities, I found the best explanation with this quote. “With the cooperation of Telit, customers can now rapidly connect different communications protocols like BACnet, OPC, Modbus or even proprietary protocols to various IoT cloud offerings such as Azure IoT, Siemens MindSphere or private cloud end points,” said Sri Rajagopal, CTO, ioTium. “All commissioning, data mapping, and contextualization can now be done remotely, dramatically reducing the time and cost of flying technicians and data scientists to the site to remediate in person.”
Then the obligatory quote from the partner. I’ve talked with Fred Yentz for many years about connecting data. Here’s his thought on this announcement. “Our alliance with ioTium establishes a best-in-class approach for digital connectivity in the industrial world,” said Fred Yentz, president Strategic Partnerships, Telit. “Together, we are providing industrial enterprise customers a secure, plug-and-play way to connect any machine to cloud-based applications to capitalize on the benefits of Industry 4.0.”
Solving this problem is mainly what the various platforms are attempting. I would be interested in hearing what is actually working out in the field. Comment or send me an email. Something is working, because engineers are doing this.
by Gary Mintchell | Aug 8, 2019 | Internet of Things, Manufacturing IT
The spread of connected devices with the resultant flow of data throughout the industrial enterprise spurs concern for security and trustworthiness of that data. The Industrial Internet Consortium (IIC) and its members recognize this problem / challenge.
I normally have a conversation with the authors of the IIC papers to get a context and sense of all the work involved in their development. In this particular case, I ran out of time. Many of you know that I am up to my eyes in soccer activities at this time of year. I just finished leading a class of new referees while I am at one of my peak times for assigning referees to games. Sometimes, I just don’t have enough hours. I bet you have never felt that…
So, IIC has published the Managing and Assessing Trustworthiness for IIoT in Practice white paper. The paper serves as an introductory guide to trustworthiness in IIoT, which is driven by the convergence of IT with OT, and includes a definition of trustworthiness, examples and a best-practice approach to managing trustworthiness in IIoT systems.
Confidence is essential to business, including confidence that the consequences of decisions and processes are acceptable and that business information is handled properly. The advent of IIoT means that confidence is also now required in technologies, physical components, and systems in addition to confidence in individuals, organizations and processes.
“The fact is that it is possible to have ‘too much’ trustworthiness,” said Jim Morrish, co-Chair of the IIC Business Strategy and Solution Lifecycle Working Group. “Trustworthiness costs, in terms of the costs of devices and associated software, and also often in terms of user experience and functionality. A trustworthiness solution for a nuclear processing plant would be an unnecessary hindrance to the day-to-day operations of a peanut butter manufacturer.”
The white paper’s best-practice approach to managing trustworthiness is comprised of four phases: baselining the system, analyzing potential trustworthiness events, implementing trustworthiness targets and governance, and iterating and maintaining the resulting trustworthiness model.
“This whitepaper demonstrates that trustworthiness is more than just another academic phrase to describe expectations of stakeholders, operators and users of an IIoT system,” said Marcellus Buchheit, President and CEO of Wibu-Systems USA, cofounder of Wibu-Systems AG in Germany and co-chair of the IIC Trustworthiness Task Group. “This paper presents several models that show how trustworthiness can be practically used in business decisions to increase trust in an IIoT system under the impact of business reality and constraints.”
The white paper also highlights that trustworthiness is not a static concept. “An IIoT system must address trustworthiness requirements throughout the lifecycle of the system. This means that industrial IoT trustworthiness is not a project with a finite start and a finite end. It is a journey that must be powered by an established program,” said Bassam Zarkout, founder of IGnPower and co-author of the paper.
“Security is already recognized as one of the most important considerations when designing an IIoT system,” said Frederick Hirsch who is a Standards Manager at Fujitsu, and also co-chair of the IIC Trustworthiness Task Group. “This white paper expands on that thinking by recognizing that safety, privacy, reliability and resilience need to be considered in conjunction with security to establish trust that IIoT systems will not only be functional but also will not harm people, the environment or society.”
The white paper discusses a live example of an IIoT system analysed from a trustworthiness perspective. Fujitsu’s Factory Operation Visibility & Intelligence (FOVI) system (and IIC testbed) has the primary goal of bringing more visibility of operations to plant managers in near-real time. The goal is to reduce human errors, bring more predictability to product assembly and delivery, and optimize production all while ensuring a sufficient level of trustworthiness.
“FOVI highlights how the different aspects of trustworthiness can impact business performance,” said Jacques Durand, Director of Engineering and Standards at Fujitsu, co-Chair of the IIC Business Strategy and Solution Lifecycle Working Group and also a member of the IIC Steering Committee. “For instance slowing down a production line can reduce costs associated with stress on machinery and machine operators, but such a course of action may also adversely impact productivity or lead time. In the white paper we highlight the need to understand trade-offs and to use metrics in a data-driven and intelligent manner.”
The Managing and Assessing Trustworthiness for IIoT in Practice white paper sets the stage for further work that the IIC will undertake focusing on trustworthiness.
The full IIC Managing and Assessing Trustworthiness for IIoT in Practice white paper and a list of IIC members who contributed can be found on the IIC website.
by Gary Mintchell | Aug 6, 2019 | Security, Standards
Standards are useful, sometimes even essential. Standard sizes of shipping containers enable optimum ship loading/unloading. Standard railroad gauges and cars enable standard shipping containers to move from ship to train, and eventually even to tractor/trailer rigs to get products to consumers.
Designing and producing to standards can be challenging. Therefore the value of Best Practices.
Taking this to the realm of Industrial Internet of Things where data security, privacy and trustworthiness are essential, the Industrial Internet Consortium (IIC) has published the Data Protection Best Practices White Paper. I very much like these collaborative initiatives that help engineers solve real world problems.
Designed for stakeholders involved in cybersecurity, privacy and IIoT trustworthiness, the paper describes best practices that can be applied to protect various types of IIoT data and systems. The 33-page paper covers multiple adjacent and overlapping data protection domains, for example data security, data integrity, data privacy, and data residency.
I spoke with the lead authors and came away with a sense of the work involved. Following are some highlights.
Failure to apply appropriate data protection measures can lead to serious consequences for IIoT systems such as service disruptions that affect the bottom-line, serious industrial accidents and data leaks that can result in significant losses, heavy regulatory fines, loss of IP and negative impact on brand reputation.
“Protecting IIoT data during the lifecycle of systems is one of the critical foundations of trustworthy systems,” said Bassam Zarkout, Executive Vice President, IGnPower and one of the paper’s authors. “To be trustworthy, a system and its characteristics, namely security, safety, reliability, resiliency and privacy, must operate in conformance with business and legal requirements. Data protection is a key enabler for compliance with these requirements, especially when facing environmental disturbances, human errors, system faults and attacks.”
Categories of Data to be Protected
Data protection touches on all data and information in an organization. In a complex IIoT system, this includes operational data from things like sensors at a field site; system and configuration data like data exchanged with an IoT device; personal data that identifies individuals; and audit data that chronologically records system activities.
Different data protection mechanisms and approaches may be needed for data at rest (data stored at various times during its lifecycle), data in motion (data being shared or transmitted from one location to another), or data in use (data being processed).
Data Security
“Security is the cornerstone of data protection. Securing an IIoT infrastructure requires a rigorous in-depth security strategy that protects data in the cloud, over the internet, and on devices,” said Niheer Patel, Product Manager, Real-Time Innovations (RTI) and one of the paper’s authors. “It also requires a team approach from manufacturing, to development, to deployment and operation of both IoT devices and infrastructure. This white paper covers the best practices for various data security mechanisms, such as authenticated encryption, key management, root of trust, access control, and audit and monitoring.”
Data Integrity
“Data integrity is crucial in maintaining physical equipment protection, preventing safety incidents, and enabling operations data analysis. Data integrity can be violated intentionally by malicious actors or unintentionally due to corruption during communication or storage. Data integrity assurance is enforced via security mechanisms such as cryptographic controls for detection and prevention of integrity violations,” said Apurva Mohan, Industrial IoT Security Lead, Schlumberger and one of the paper’s authors.
Data integrity should be maintained for the entire lifecycle of the data from when it is generated, to its final destruction or archival. Actual data integrity protection mechanisms depend on the lifecycle phase of the data.
Data Privacy
As a prime example of data privacy requirements, the paper focuses on the EU General Data Protection Regulation (GDPR), which grants data subjects a wide range of rights over their personal data. The paper describes how IIoT solutions can leverage data security best practices in key management, authentication and access control can empower GDPR-centric privacy processes.
The Data Protection Best Practices White Paper complements the IoT Security Maturity Model Practitioner’s Guide and builds on the concepts of the Industrial Internet Reference Architecture and Industrial Internet Security Framework.
The Data Protection Best Practices White Paper and a list of IIC members who contributed to it can be found on the IIC website
