by Gary Mintchell | Jan 24, 2020 | Data Management, Manufacturing IT
Digitization is on everyone’s lips these days. If you have not taken steps to implement and improve digital data flow, you are probably already behind. I receive information regularly from PwC and here is a new report on how digitization is reshaping the manufacturing industry. The report takes a look at 8 companies and showcase how they improved their efficiency, productivity and customer experience by ensuring they have the right capabilities central to their operating model and by matching them with strong skill sets in analytics and IT.
Pressure from the consumer, new regulations and advances in information technology are all reasons that are pushing manufacturing organizations to digitize so they can avoid falling behind the new breed of market-leading ‘digital champions.’ The report identifies 4 significant changes CEOs must implement to maximize the benefits of digitization.
1. Drive organizational changes that address new digital capabilities and digitalized processes – e.g., product and process design and engineering, end-to-end procurement, supply chain/distribution and after-sales – right from the top, because these are so new and different
2. Hire more software and Internet of Things (IoT) engineers and data scientists, while training the wider workforce in digital skills
3. Learn from software businesses, which have the ability to develop use cases rapidly and turn them into software products
4. Extend digitalization beyond IT to include significant operational technologies (OT) such as track and trace solutions and digital twinning
From the report, “Already, digitally ‘smart’ manufacturers are gaining a competitive advantage by exploiting emerging technologies and trends such as digital twinning, predictive maintenance, track and trace, and modular design. These companies have dramatically improved their efficiency, productivity, and customer experience by ensuring these capabilities are central to their operating models and by matching them with strong skill sets in analytics and IT. “
During 2018 and early 2019, PwC conducted in-depth digitisation case studies of eight industrial and manufacturing organisations in Germany, the US, India, Japan and the Middle East. Drawing on discussions and interviews with CEOs and division heads, we explored the key triggers for change these companies faced, assessed how digital solutions are being implemented and how digitisation is affecting key aspects of their operating models. We also compared our eight organisations with other publicly cited digitisation case studies, and leveraged PwC’s 2018 study Digital Champions: How industry leaders build integrated operations ecosystems to deliver end-to-end customer solutions and other ongoing PwC research.
This paper is the result of ongoing collaboration between PwC and the Global Manufacturing and Industrialisation Summit (GMIS). GMIS provides a forum for industry leaders to interact with governments, technologists and academia in order to navigate the challenges and opportunities brought about by the digital technologies of the Fourth Industrial Revolution. PwC has been a knowledge partner with GMIS since 2016.
The eight case studies in this report make clear how far the role of digital technology goes beyond traditional IT systems. It also encompasses OT and data and analytics technologies. Full integration and linkage among these different technologies, and the ecosystems they are part of, are essential to a successful digital transformation. Yet success is impossible without a digitally smart workforce that is familiar with Industry 4.0 skills and tools.
These challenges are the subject of the second part of the report Digital Champions: How industry leaders build integrated operations ecosystems to deliver end-to-end customer solutions, which will be published in January 2020.
The report will elaborate further on the emerging theory of digital manufacturing and operations, in which successful, digitised industrial organisations will increasingly have to act like software companies in response to four key factors:
- The connected customer seeks a batch size of one, necessitating greater customisation of products and delivery time, improved customer experience, use of online channels and outcome-based business models.
- Digital operations require both engineering and software abilities to enable extensive data analysis and IoT-based integration, as well as digitisation of products and services.
- Organisations need augmented automation, in which machines become part of the organisation via closely connected machine–worker tasks and integrated IT and OT.
- Future employees will be ‘system-savvy craftspeople’ with the skills to use sensors in order to collect and analyse accurate data, as well as design and manage connected processes.
About the authors
Anil Khurana is PwC’s global industrial, manufacturing and automotive industry leader. He is a principal with PwC US.
Reinhard Geissbauer is a partner with PwC Germany based in Munich. He is the global lead for PwC’s Digital Operations Impact Center.
Steve Pillsbury is a principal with PwC US and the US lead for PwC’s Digital Operations Impact Center.
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 16, 2019 | Automation, Internet of Things, Manufacturing IT, Operations Management, Technology
The short take: ADVICS and Macnica Networks, Inc. deploy FogHorn Edge Computing Software in Smart Factory Transition. We talk endlessly about IoT, digital transformation, and now Smart Factory Transition. Do these terms mean anything? I think we are seeing people do actual work by using digital technologies that they mostly already have pieces of. Then marketers come along and christen it with a name. We are witnessing real progress improving manufacturing and production with modern thinking and tech.
In this case according to the press release, a $5B automotive brake system manufacturer deploys FogHorn Lightning Edge Computing Software Platform for real-time data processing, machine learning and AI. Note: machine learning is usually considered a subset of AI.
ADVICS Co. Ltd., working with Macnica Networks Inc., has deployed FogHorn Lightning Edge Computing Software to provide onsite data processing, real-time analytics, and ultimately machine learning AI in its smart factory transition.
ADVICS supplies advanced, high-quality automotive brake systems and components globally. ADVICS partnered with Macnica Networks to digitize its manufacturing sites and integrate varied equipment data to enable edge-based real-time visualization and analytics of its manufacturing. The digital transformation has allowed ADVICS to identify production issues immediately and quickly determine the root cause therefore improving manufacturing efficiencies. Manual workloads surrounding data acquisition have also been significantly reduced, enabling operation leaders to spend more time on managing production.
“ADVICS digital transformation to a smart factory reflects their mission to contribute to the reliability of society by pursuing a better safety, environment and comfort through products that delight customers,” said Yuta Endo, vice president, general manager of business development and head of APAC operations at FogHorn. “We are excited to work with our partner, Macnica Networks, to help ADVICS enhance manufacturing efficiency. FogHorn Lightning is uniquely positioned to help companies transform streaming data into actionable, predictive insights right at the edge, providing real-time monitoring and diagnostics, streaming analytics, machine learning and operations optimization.”
FogHorn’s Lightning product portfolio embeds edge computing software locally, as close to the source of streaming sensor data as possible. FogHorn Lightning Edge platform delivers low latency for onsite data processing and real-time analytics in addition to its machine learning and artificial intelligence (AI) capabilities.
ADVICS is one of the 13 major Aisin Group companies. The main business is the development, production and sales of automotive brake systems and parts that make up these systems.
Macnica Networks is a member of the Macnica Group, a growing global technology distributor. The company has over 20 years of experience in product localization, sales, and technical support of computer network equipment. It supplies a full line of leading-edge network appliances, software, telecom solutions to its customers, and consistently brings innovative new products to their portfolio.
FogHorn is a developer of edge computing software for industrial and commercial IoT application solutions.
by Gary Mintchell | Jul 10, 2018 | Automation, Commentary
Rockwell Automation’s recent huge investment in PTC for only 8% of the company has sparked a number of thoughts on strategies not only of Rockwell Automation, but also other companies in the market. We’re looking not only at Rockwell Automation in this brief analysis, but also Siemens, Schneider Electric, and ABB.
I’ve left out Emerson, Honeywell, and Yokogawa. The only interesting thing in that part of the market is Emerson’s abortive run at acquiring Rockwell. That was strange. I don’t think that Emerson could have digested such a meal.
The analysis is not to knock anyone but to look for trends and strategies of some of our major suppliers.
I think it begins with Siemens. An executive explained the company’s digital factory strategy and vision many years ago. Then the company acquired UGS and added PLM, CAD, and other digital technologies. There followed other similar acquisitions. I’m thinking mainly of the COMOS product, here.
If you are looking for an articulation of the strategy, I suggest looking no further than Industrie 4.0 and cyber-physical systems.
Sticking with Europe and the competition over there, let’s consider Schneider Electric. This company has been building the “electrification” side of the business which also brought industrial control products and some automation–think Modicon. While it lost considerable market share in PLCs, it did remain in the market. Then it acquired Invensys adding a lot of software (something it never really was good at) but especially process control (Foxboro, etc.). This latter helps it in the power market segment and positions it well against ABB. Siemens of course is the main competitive target. Then is a strange move, Schneider used its software businesses (Wonderware, etc.) as an investment in AVEVA grabbing 51% of the company. Now it, too, has a digital factory strategy in place.
ABB, a strong competitor in the power side of the business and also in process control, acquired B+R Automation. That company was a strong second-tier machine automation supplier fleshing out ABB’s portfolio in the discrete, or machine, automation market. Then it acquired GE’s industrial business strengthening ABB in the “electrification” market. Sounding familiar.
Now look at Rockwell’s investment. That company has flirted with Dassault Systemes over many years for a PLM-to-Control strategy. But nothing ever came of it.
A couple of years ago it acquired thin-client manufacturer ACP and systems integrator Maverick Technologies and MagneMotion a supplier of motion control and conveyor technologies. Then came a large investment in PTC for a small percentage of the company. I speculated that this could be a Digital Factory play along with the respected analyst Joe Barkai, but my friend Keith Larson writing for Putman Publishing (and someone I trust to accurately report on what suppliers are saying) reported that the sought-after prize was a closer integration with ThingWorx. This would be a piece of the Rockwell strategy of “Connected Enterprise” and Larson reported that the target RA product is its MES offering.
In other words, Rockwell Automation seems focused not on the current buzz of Industry 4.0/Industrial Internet of Things/Cyberphysical systems/Digital Factory, but on “making our customers more productive.” Its roots are plant floor and it remains a plant floor supplier.
I am NOT predicting any acquisition of Rockwell Automation, but I do believe that the market needs some continued consolidation. The next five years will be interesting in this market.
by Gary Mintchell | Mar 2, 2018 | Automation, Internet of Things, Operations Management, Process Control, Safety, Security, Technology
Let me try to summarize a number of other news items gleaned from the ARC Forum featuring edge computing, IIoT Platforms, and technology. When ARC’s Paul Miller told me it would be the best ever, he turned out not to be exaggerating. More people, more news.
Stratus Technologies, known for years for secure servers, released an edge computing device. Interest in computing at the edge of the network has blossomed lately, with many companies releasing products. Lots of choices for users.
Integration Objects, firmly within another important trend, introduced an Industrial Internet of Things (IIoT) Platform. I’m beginning to see articles about users latching on to these platforms rather than building their own ad hoc connections among IoT devices and applications.
UL discussed standards with me during the show. The company known for developing safety standards and then testing for compliance has developed also a security standard. And it tests to it for compliance.
HIMA is another company combining safety and security technologies. There is so much in common between the two–especially thought processes and planning.
Yokogawa has extended and rebranded its process automation offering, now called Synaptic Business Automation. Among other things, it has refined the dashboard into a “karaoke” style.
Bentley Systems discussed the combining of engineering design tools with digital photography and other digital technologies to better represent the engineering and design of a plant. This is the most cutting edge technology I saw during the week, but I cannot do it justice in a paragraph. I encourage a tour of the Website.
