by Gary Mintchell | Oct 19, 2019 | Automation, Internet of Things, Technology, Uncategorized
This is still more followup from Emerson Global Users Exchange relative to sessions on Projects Pilot Purgatory. I thought I had already written this, but just discovered it languishing in my drafts folder. While in Nashville, I ran into Jonas Berge, senior director, applied technology for Plantweb at Emerson Automation. He has been a source for technology updates for years. We followed up a brief conversation with a flurry of emails where he updated me on some presentations.
One important topic centered on IoT projects—actually applicable to other types of projects as well. He told me the secret sauce is to start small. “A World Economic Forum white paper on the fourth industrial revolution in collaboration with McKinsey suggests that to avoid getting stuck in prolonged “pilot purgatory” plants shall start small with multiple projects – just like we spoke about at EGUE and just like Denka and Chevron Oronite and others have done,” he told me.
“I personally believe the problem is when plants get advice to take a ‘big bang’ approach starting by spending years and millions on an additional ‘single software platform’ or data lake and hiring a data science team even before the first use case is tackled,” said Berge. “My blog post explains this approach to avoiding pilot purgatory in greater detail.”
I recommend visiting Berge’s blog for more detail, but I’ll provide some teaser ideas here.
First he recommends
- Think Big
- Start Small
- Scale Fast
Scale Fast
Plants must scale digital transformation across the entire site to fully enjoy the safety benefits like fewer incidents, faster incident response time, reduced instances of non-compliance, as well as reliability benefits such as greater availability, reduced maintenance cost, extend equipment life, greater integrity (fewer instances of loss of containment), shorter turnarounds, and longer between turnarounds. The same holds true for energy benefits like lower energy consumption, cost, and reduced emissions and carbon footprint, as well as production benefits like reduced off-spec product (higher quality/yield), greater throughput, greater flexibility (feedstock use, and products/grades), reduced operations cost, and shorter lead-time.
Start Small
The organization can only absorb so much change at any one time. If too many changes are introduced in one go, the digitalization will stall:
- Too many technologies at once
- Too many data aggregation layers
- Too many custom applications
- Too many new roles
- Too many vendors
Multiple Phased Projects
McKinsey research shows plants successfully scaling digital transformation instead run smaller digitalization projects; multiple small projects across the functional areas. This matches what I have personally seen in projects I have worked on.
From what I can tell it is plants that attempt a big bang approach with many digital technologies at once that struggle to scale. There are forces that encourage companies to try to achieve sweeping changes to go digital, which can lead to counterproductive overreaching.
The Boston Consulting Group (BCG) suggests a disciplined phased approach rather than attempting to boil the ocean. I have seen plants focus on a technology that can digitally transform and help multiple functional areas with common infrastructure. A good example is wireless sensor networks. Deploying wireless sensor networks in turn enables many small projects that help many departments digitally transform the way they work. The infrastructure for one technology can be deployed relatively quickly after which many small projects are executed in phases.
Small projects are low-risk. A small trial of a solution in one plant unit finishes fast. After a quick success, then scale it to the full plant area, and then scale to the entire plant. Then the team can move on to start the next pilot project. This way plants move from PoC to full-scale plant-wide implementation at speed. For large organization with multiple plants, innovations often emerge at an individual plant, then gets replicated at other sites, rolled out nation-wide and globally.
Use Existing Platform
I have also seen big bang approach where plant pours a lot of money and resources into an additional “single software platform” layer for data aggregation before the first use-case even gets started. This new data aggregation platform layer is meant to be added above the ERP with the intention to collect data from the ERP and plant historian before making it available to analytics through proprietary API requiring custom programming.
Instead, successful plants start small projects using the existing data aggregation platform; the plant historian. The historian can be scaled with additional tags as needed. This way a project can be implemented within two weeks, with the pilot running an additional three months, at low-risk.
Think Big
I personally like to add you must also think of the bigger vision. A plant cannot run multiple small projects in isolation resulting in siloed solutions. Plants successful with digital transformation early on establish a vision of what the end goal looks like. Based on this they can select the technologies and architecture to build the infrastructure that supports this end goal.
NAMUR Open Architecture (NOA)
The system architecture for the digital operational infrastructure (DOI) is important. The wrong architecture leads to delays and inability to scale. NAMUR (User Association of Automation Technology in Process Industries) has defined the NAMUR Open Architecture (NOA) to enable Industry 4.0. I have found that plants that have deployed digital operational infrastructure (DOI) modelled on the same principles as NOA are able to pilot and scale very fast. Flying StartThe I&C department in plants can accelerate digital transformation to achieve operational excellence and top quartile performance by remembering Think Big, Start Small, Scale Fast. These translate into a few simple design principles:
- Phased approach
- Architecture modeled on the NAMUR Open Architecture
- Ready-made apps
- East-to-use software
- Digital ecosystem
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
by Gary Mintchell | Aug 29, 2018 | Internet of Things, Standards
Industrial Networking Enabling IIoT Communication white paper
Working consortia of companies and individuals researching a technology provide great guidance for users of the technology—usually in the form of white papers. The Industrial Internet Consortium (IIC) has been especially prolific lately. This means many companies and individuals see the importance of donating time and expertise to the cause.
The IIC has announced the IIC Industrial Networking Enabling IIoT Communication white paper. The paper serves as an introductory guide on industrial networking for IIoT system designers and network engineers, and offers practical solutions based on key usage scenarios.
“Industrial networking is the foundation of IIoT,” said David Zhe Lou, Chief Researcher, Huawei Technologies. “There are many choices of networking technologies depending on the application, the industrial network, deployment situation and conditions, but there is no universal or preferred industrial networking solution.”
Industrial networking infrastructure and technologies reside at the IP layer and below, and enable industrial assets, such as machines, sites and environments, to connect to the business professionals supporting applications across a wide range of industry sectors. Industrial networking technologies provide the foundation for applications that enable manufacturing productivity and profitability.
“IIoT applications have different needs depending on the industrial application and therefore demand robust, flexible and secure networks,” said Cliff Whitehead, Business Development Manager, Rockwell Automation. “This white paper will help IIoT system designers and network engineers understand the tradeoffs they can consider when designing an industrial network architecture that will be a strong foundation for current and future IIoT scenarios.”
Industrial networking is different from networking for the enterprise or networking for consumers. For example, IIoT system designers and network engineers need to make decisions about using wired or wireless communications. They have to figure out how to support mobility applications such as vehicles, equipment, robots and workers. They must also consider the lifecycle of deployments, physical conditions, such as those found in mining and agriculture, and technical requirements, which can vary from relaxed to highly demanding.
“Networking technologies range from industry-specific to universal, such as the emerging 5G, which meets diverse industrial needs,” continued Jan Höller, Research Fellow at Ericsson. “Industrial developers need guidance when devising solutions to select the right networking technologies, and this white paper is the first step to providing the missing methods and tools.”
The Industrial Networking Enabling IIoT Communication white paper sets the stage for the Industrial Internet Network Framework (IINF), which will complement the Industrial Internet Connectivity Framework (IICF) by detailing requirements and best available technologies for the lower three layers of the industrial internet communication stack.
The full IIC Industrial Networking Enabling IIoT Communication white paper and a list of IIC members who contributed can be found on the IIC website:
The Industrial Internet Consortium is a program of the Object Management Group (OMG).
by Gary Mintchell | Jun 18, 2018 | Internet of Things, Manufacturing IT
The Industrial Internet Consortium (IIC) generates much useful information promoting awareness and technical tips about, well, the Industrial Internet of Things. Last week I had the opportunity to speak to the authors of a new white paper, ”Introduction to Edge Computing in IIoT”, Todd Edmunds, Senior Solution Architect, IoT, Cisco, and Lalit Canaran, VP, SAP.
The paper provides practical guidance on edge computing, architectures and the building blocks necessary for edge computing implementations. The IIC is also planning to release an Edge Computing Technical Report that will contain in-depth technical information in the coming months.
This paper is not a C-level generic paper evangelizing the concept, but rather practical advice designed to open the discussion followed by technical details targeted to those to whom the C-level executives might tell, “I have been reading about the IIoT. This looks like something we should be jumping into.”
We discussed how the edge should be defined by the business objective rather than the technology used. Using computing at the edge improves performance of the system when bandwidth could be the constraining factor for using the cloud.
As the edge gets more powerful, they told me, the role of the cloud will shift to one of orchestration of remote sites plus storage.
“Many companies are wanting to realize the business benefits that edge computing is purported to provide but are unsure where to begin or how to realize those advantages. The IIC has been at the vanguard of the industrial internet since its inception, and edge computing has been an integral part of driving the transformational outcomes that go along with it,” said Edmunds. “With the publication of this white paper, we provide practical guidance on where the ‘edge’ is and the key drivers for implementing edge computing. We also provide detail on edge computing architectures and real-world use cases.”
“Almost every use case and every connected device on the industrial internet requires some sort of compute capability at its source at the edge,” said Dr. Mitch Tseng, Distinguished Consultant, Huawei Technologies, and co-author of the white paper. “Oil rigs in remote locations have sensors gathering data but they need to be mindful of the challenges of data transmission because of bandwidth issues or the cost of transmission. The white paper is a first step in the development of an industrial grade ‘cookbook’ for edge computing.”
“Organizations adopting an IIoT strategy need to understand what data is available, how to use it to drive industrial processes and how to orchestrate, manage and secure data/compute,” said Canaran. “This paper and subsequent technical report will enable enterprises to unlock the full potential of the edge-cloud continuum and drive the business outcomes enabled by next-generation IoT devices, machine learning and AI.”
The full IIC Introduction to Edge Computing in IIoT white paper and a list of IIC members who contributed can be found on the IIC website.
