by Gary Mintchell | Jun 3, 2021 | Enterprise IT, Manufacturing IT, Operations Management, Software
Senior management have always been reluctant to invest in technology and especially upgrades once a technology is in place. I have seen instances where management lays off the senior engineers who implemented something like Advanced Process Control or Manufacturing Execution Systems keeping a recent graduate engineer to maintain the system, if even that. Management sees only a large salary cost reduction. Rarely is maintaining momentum a virtue.
I have been in way too many of these discussions in my career. I’ve seen results one way or another. There have been the instances where they had to hire back the laid off engineer at higher consultant rates to get the system back up and running properly.
So, this report from CIMdata detailing research on PLM software upgrading was hardly surprising. Disturbing, perhaps, but not surprising.
Digital transformation is a popular topic, and CIMdata has written much about it. While many still wonder whether digital transformation is real or just the latest buzzword, many industrial companies are taking its promise very seriously.
While it is clear to all within the PLM community that PLM is foundational to a meaningful digitalization program (or digital transformation strategy), this truth is not always understood by senior leadership within companies. While CIMdata believes that the level of investment in digital transformation is appropriate, based on our research and experience we find that executive awareness of the dependency of digital transformation on PLM is lacking. This lack of understanding of its association to PLM-related investment, sustainability and impacts on business performance and benefits puts many digital transformation programs at risk of becoming yet another program of the month.
This research on obsolescence identified areas that increased the cost of technology refresh and found that heavy customization was at the top of the list. This aligns with CIMdata’s experience in the field and is why companies strive to be more out-of-the-box with their PLM implementations. CIMdata’s view is that customization can add significant value to a PLM implementation, but it needs to be either business or cost justified and deliver an appropriate return on investment over the long-term (i.e., even through subsequent solution upgrades).
A new study from CIMdata exposes the financial risk many organizations face when they take PLM upgrades for granted. According to the study, the cost of upgrades with legacy PLM vendors can average between $732,000 and $1.25 million. The study – which compares industry heavyweights such as Dassault, PTC, and Siemens – finds the Aras PLM platform is easiest to keep current. Aras users upgrade more frequently, over a shorter duration, and at less cost than other leaders in the space.
What’s behind PLM obsolescence? According to CIMdata, “A sustainable PLM solution is one that can meet current and future business requirements with an acceptable return on investment (ROI) via incremental enhancements and upgrades.” But as clearly shown in the research, many companies using PLM software are not staying current. The five reasons are:
1. Technically Impossible. Typically, after an arduous deployment and the necessary customization to meet the businesses current needs, the software is no longer capable of upgrading.
2. No ROI. If you take a year to upgrade and it costs close to a million dollars, the cost and impact to the business is so outrageous it can’t be justified.
3. No Budget. Not having the budget is a real concern, but often the lack of budget is a mistake—a mis-prioritization of what’s important to your organization’s future growth, often combined with a high percentage of the overall budget being consumed by technical debt.
4. Companies overinvest and therefore are committed. The only thing worse than spending large amounts of money on the wrong thing is doubling down and spending more, expecting a better experience. The pandemic has accelerated the need to change, to expect transformation with less risk, less cost, and greater ROI that will lead to greater business resiliency. Throwing good money after bad is no longer being tolerated—there is more of a focus on the bottom-line and doing more with less.
5. Leadership Doesn’t Understand Dependency of Digital Transformation on PLM. If your PLM system hasn’t been upgraded in years and isn’t the foundation for continuous digital transformation efforts, there is an absolute lack of understanding of how PLM can transform a business.
by Gary Mintchell | May 19, 2021 | Data Management, Manufacturing IT, Operations Management, Software
I have not talked with anyone from Rockwell Automation for months. So, it was time to catch up with Keith Higgins who joined the company within the past couple of years as VP of Digital Transformation leading the software group. As we might expect, digital transformation technologies and products include the analytics portfolio, MES, and the coordination with PTC’s products including ThingWorx, Kepware, and Vuforia.
Since I was fresh from a conversation with another supplier about the Edge, I brought that up in the context of analytics and ThingWorx. Higgins began to explain the power of using the PLC as an edge device. Rockwell has not talked to me for years about the PLC, but I remember that for years it has added compute and networking capability into that platform. Time for me to get an update there, too. My wild guess is that no sufficiently enticing partnership could be hacked out with Dell Technologies or HPE using their Edge compute. And, they already had a powerful Edge device that just needed IT-level bolstering. This will be interesting to watch.
Higgins brought up a tire plant example where having production data in context at the edge with the ability to perform predictive analytics combined for a powerful management tool.
One theme that recurs in this discussion in general is the necessity for solid context for data. Higgins having brought that up regarding the tire plant example, continued to a discussion of a technology/product developed in partnership with Microsoft called SmartObjects. This is a rich data model that adds deep context to data. My feeble way of thinking of this would be something like a modern data model like MQTT and OPC UA on steroids (no disparagement of either of those technologies meant).
I’ve been thinking deeply about productivity lately, so I asked about it. Rockwell views its contribution to its customers’ productivity in three buckets:
- Assets—building on predictive analytics, predictive maintenance, condition monitoring, and the like;
- Production line—improving utilization of the production assets;
- Human productivity—for example, the recent acquisition of CMMS supplier Fiix
I’m definitely interested in seeing where Rockwell’s new emphasis in software and edge goes. Many years ago, I asked then-CEO Keith Nosbusch about the software business. He said at that time it was an experiment. Higgins didn’t say that exact thing, but his remarks left no doubt that his area is primed to be a Rockwell growth vehicle.
by Gary Mintchell | May 5, 2021 | Internet of Things, Manufacturing IT, Operations Management, Software, Uncategorized
Back in the 90s, I used to haul around a $25,000 vision system in the trunk of my car to perform demonstrations of machine vision technology applications.
Today, there is more video power in my smartphone than in that entire system.
Just like all the technologies we use in manufacturing, vision systems and video have become more powerful and useful,most often leveraging consumer electronics or IT innovations. I visited a small chemical refinery that installed streaming video into its operator interface for a unique, but essential, personnel safety/security application. Located in a rural area of Texas, the refinery operators periodically opened the gates to allow railway cars into the facility or to let the filled cars leave. The open gates became a welcome invitation to the local coyote population. Of course, these guys were not wanted wandering around the facility. The video system watched for incursions and alerted personnel.
Not too long ago, the bandwidth required by that streaming video would have been too expensive or awkward to be economical. Now, it’s just another sensor.
Intelligent Video for Health and Safety
These Covid pandemic days have led to new use cases for video. AT&T identifies a few key examples on their video intelligence page:
- Ensuring social distancing
- Counting people to maintain safe capacity
Infrared thermal imaging has progressed to the point that strategically placed thermal imaging cameras can monitor personnel for fevers—an outward sign of potential Covid infection. We can potentially stop the spread of the virus at the plant entrance.
Another Covid-related application involves contact tracing and social-distancing assurance. These applications require high bandwidth along with sophisticated analysis software—both now readily available. And, both technologies are poised for improvement. We will see 5G installations before long that will improve bandwidth, speed, and latency forvideo applications.
“Outside of these pandemic applications, process plants with hazardous areas have found video sensors to be a perfect solution to determining personnel safety during an incident. Rescue teams need to know who is in the area and where they are. Security teams can be alerted if someone wanders into a hazardous or restricted area.
Intelligent Video for Quality Control
Then we return to the applications I once tried to solve—product quality. While it is best practice to fix the process such that defects are not produced, vision inspection is another step in assuring products that fail to meet specification are not shipped to customers. Taking a feedback loop from inspection information provides a pathway to solving the process problem. As network bandwidth improves and video sensors become smaller, cheaper, faster, these video IoT solutions become more attractive.
5G is the Foundation
Apple released its latest iPhone (one of which is lying on my desk) with great hoopla about 5G. Apple pundits were originally less than enthusiastic about the 5G bandwidth. I have been advising them, along with clients and readers,about the tremendous value that will be unlocked by 5G. It may not be as apparent in an individual iPhone, but we will see a massive shift in business and manufacturing applications.
5G skeptics do exist, but most technologists are decidedly bullish on the possibilities. I think that manufacturers of many varieties will begin deploying the networks for one or two of the reasons that fit them, and then discover that they’ve received more benefit than they expected. Then managers and engineers will have difficulty remembering why there was any debate over moving from LTE to 5G.
As the AT&T Business team puts it in their “Agility Refined” white paper:
5G is the next generation of wireless communications technology. In essence, 5G will put the network edge closer to users and devices. It uses mid-band frequencies and millimeter wave (mmWave) to help accomplish this.
5G offers significantly larger spectrum allocations and enables exponentially increased data rates. It has a reduced range compared to today’s 4G frequencies—but the antennae needed for 5G are much smaller. This will allow for a dense network of small cells, enhancing the current user experience.
As you lay out your 5-year-and-beyond scenarios, this intelligent video powered by 5G will be technology to keep in the narrative.
This post was sponsored by AT&T Business, but the opinions are my own and don’t necessarily represent AT&T Business’s positions or strategies.
by Gary Mintchell | Apr 28, 2021 | Operations Management, Software
As part of my Hannover Messe interviews a couple of weeks ago, John Gonsalves, a VP at Cyient, introduced me to “our answer to Industry 4.0” for connected workers and supply chain. The new product is INTELLICYIENT, a suite of Industry 4.0 solutions that will enable digital transformation for industries that draw significant value from their assets such as manufacturing, industrial, aerospace, automotive and off-highway, utilities, and mining and natural resources.
Gonsalves, “The most successful Industry 4.0 solutions will be the ones that bring domain knowledge, depth of technological expertise, and engineering excellence and understanding of business operations. These have been the unique strengths of Cyient, which makes it a partner of choice across its Fortune 500 customers globally.”
Commenting on the launch, Anand Parameswaran, SVP and Global Business Head, Cyient Digital, said, “Cyient has leveraged its investments in the latest digital technology capabilities, and its three decades of experience in engineering and geospatial offerings for asset-intensive industries to design its INTELLICYIENT solution portfolio. With six digital solutions, powered by the interplay of nine technology studios, and our strong partner ecosystem, INTELLICYIENT will help enterprises globally achieve the full potential of digital transformation with IT-OT convergence. We aim to focus on the four key themes of smart automation, intelligent supply chain, end-to-end visibility of workflows and assets, and next-gen workforce solutions that are driving Industry 4.0 adoption.”
Akshat Vaid, Vice President, Everest Group, added, “Digital engineering has become all-pervasive, contributing over 23% to global ER&D spending. Within manufacturing, it manifests as Industry 4.0—the transformation of cyber and physical systems on the back of digital themes for enhanced visibility, control, and autonomy. Industry 4.0 investments have been rising steadily, and the COVID-19 crisis has provided an additional impetus as enterprises look to enhance manufacturing resilience. In effect, enterprises are no longer viewing this spend as discretionary but rather as an avenue for driving business resilience and competitiveness. They, however, struggle with a shortage of capabilities, organizational complexity, data integration, and speed of implementation when it comes to transformation-at-scale. This has led to a rise in outsourcing with third-party vendors offering services across consulting, development, integration, and management of existing deployments.”
Cyient is a global engineering and digital technology solutions company. As a Design, Build, and Maintain partner for leading organizations worldwide, Cyient takes solution ownership across the value chain to help customers focus on their core, innovate, and stay ahead of the curve. The company leverages digital technologies, advanced analytics capabilities, domain knowledge, and technical expertise to solve complex business problems. Cyient partners with customers to operate as part of their extended team in ways that best suit their organization’s culture and requirements. Cyient’s industry focus includes aerospace and defense, medical technology and healthcare, telecommunications, rail transportation, semiconductor, geospatial, industrial products, and energy and utilities.
by Gary Mintchell | Apr 27, 2021 | Automation, Software
I have witnessed the evolution of Optical Character Recognition (OCR) over the past 35 years. This is an automated system of taking a picture in a digital vision system of some text, doing some magic processing, and outputting machine understandable text that can be used directly in your software application.
Neurala discovered this website’s reach and has been sending me a stream of updates. This is a company moving forward rapidly. Today’s announcement pushes the state-of-the-art.
Today, Neurala announced a partnership with IHI Logistics & Machinery. Neurala’s vision AI software will be deployed to increase the effectiveness of optical character recognition (OCR) reading of package information by automatically identifying expiration dates, to ultimately reduce waste and relieve workers from mundane, repetitive tasks.
IHI Logistics & Machinery is a leading global provider of material handling and factory automation solutions, with a focus on the management of food packaging information and logistics process improvement specifically. Traditionally, food and perishable items come into the warehouse with a production and an expiration date, with these important dates scanned by human workers with handheld OCR terminals upon arrival. It is a tedious job, and when an OCR terminal misreads an expiration date, it results in the need for inspection by humans. This also increases manufacturers’ costs and reduces profits.
Neurala’s vision AI will improve OCR by automatically identifying a product’s expiration date, including validating where on the packaging the expiration date is located. It will also be able to verify that text on a box is the expiration date, as opposed to other numerical data such as the SKU or production date, if a series of dates is present. This reduces the need for manual intervention when errors or misreads occur and ensures that only accurate data is passed back to the ERP system.
“Introducing AI and automation into our workflow will be a game changer for our business,” said Takayuki Sado, general manager at IHI Logistics & Machinery. “By partnering with Neurala, we are able to bolster our value to our customers, by dramatically increasing the speed and efficiency of material handling. This level of automation is also extremely valuable, as it helps us do more with less – which is especially critical in a time when there are restrictions limiting the number of workers present on the warehouse floor.”
“Neurala is on a mission to help manufacturers realize the benefits of vision AI by partnering with companies around the world who are leaders in their industry,” said Max Versace, co-founder and CEO of Neurala. “We are excited to partner with IHI Logistics & Machinery to provide them with the technology needed to further their position as an innovator and leader in material handling.”
by Gary Mintchell | Mar 31, 2021 | Manufacturing IT, News, Operations Management, Software
Seeq has developed some pretty cool analytics solutions. This announcement seems to be just some repackaging and rebranding of components, but it serves as a refresher for its suite of products.
New editions address end-user deployment requirements from individual plants and facilities
to multi-plant enterprise and cloud deployments.
Seeq Corporation, a leader in manufacturing and industrial internet of things (IIoT) advanced analytics software, announces a new packaging of Seeq features and applications as Seeq Team and Seeq Enterprise editions. These editions address the needs of customers from a local water utility to a multi-national chemical, pharmaceutical, or oil & gas company.
Both Seeq editions, which run best as SaaS on AWS or Microsoft Azure, represent the culmination of learning and experiences with hundreds of Seeq deployments in process manufacturing organizations. For these manufacturers, Seeq enables advanced analytics insights to improve production and business outcomes across their organizations.
Seeq Cortex, a renaming of Seeq Server, is included in both editions and is the execution engine that delivers key features, including multi-source and type data connectivity, security, calculation scalability, and other features. Seeq Cortex ensures immediate and long-term support for customer data architectures and IT requirements.
“Seeq Cortex enables immediate access to analytics innovation with existing data architectures and silos, while also supporting customer data roadmaps and strategies on the cloud,” says Steve Sliwa, CEO and Co-Founder Seeq Corporation. “Cortex is the backbone of the predictive, diagnostic, machine learning, and descriptive analytics used by customers around the globe.”
Cortex benefits include:
· Abstraction of data sources with high-speed connectivity to multiple and diverse time series and contextual data sources, including historians and SQL-based data sources.
· Calculation speed with a highly parallelized, time-series specific engine to enable fast execution of analytics including data interpolation, filtering, cleansing, and modeling.
· Data security and user access control through integration with OSIsoft PI for tag-level access control, or organizations may implement their own governance policies.
Seeq Team is optimized for new deployments in a single site facility such as a water utility or power generation plant with a limited number of time series and contextual data sources, or for the first usage of Seeq by a workgroup within a larger organization. Quick and easy deployment of Seeq and resulting ROI will demonstrate the benefit of leveraging existing data and expertise to improve production outcomes.
Seeq Enterprise is designed for complex single-plant, multi-site, or enterprise deployments with hundreds or thousands of users. It includes support for more complex data sources such as data lakes and ERP systems, along with features for integrating OT and IT data science teams driving digital transformation initiatives. Features specific to Seeq Enterprise include:
· Seeq Data Lab is built on Jupyter Notebooks to enable easy Python access to Seeq functionality and to the vast library of open source modules and algorithms.
· Unlimited Seeq users: Seeq Enterprise does not have a limit on number of users.
· More and complex data sources: Seeq Enterprise supports up to 10 connections including data sources such as data lakes, ERP, and non-SQL databases.
· Audit trail support: Seeq Enterprise includes features and administration tools for customers in regulated industries including support for CFR Part 11.
· Data visualization tools: Seeq Enterprise supports data integration with BI and process applications such as Tableau, PowerBI, Spotfire and OSIsoft PI Vision.
In addition to support for large deployments with Seeq Enterprise, Seeq also has a licensing option for indirect usage of Seeq through its REST API and related software development kits for Java, C#, and Python, and Seeq connectivity to more than 10 enterprise data sources. This license, the Seeq Strategic Agreement, is appropriate for Seeq customers who require these capabilities and are making a multi-year commitment to Seeq success within their organization
“Seeq continues to release compelling analytics solutions for end users in process manufacturing and Industry 4.0 engagements,” comments Janice Abel, Principal Analyst at ARC Advisory Group. “The need for the faster and better insights provided by Seeq is a consistent requirement for organizations investing in IIoT and Smart Manufacturing.”
Seeq’s rapid growth is being fueled in part by its partnerships and commitment to cloud-based computing. Seeq is available in the AWS marketplace and is an AWS Industrial Competency Partner. On Microsoft Azure, Seeq has been available in the Azure Marketplace since 2019 and was recognized last year as a 2020 Microsoft Energy Partner of the Year Finalist.
