By Bill Zujewski
This is the second post in a multi-part series, which specifically explores the challenges of dealing with wireless technology as part of an M2M (Machine-To-Machine) initiative. The series will offer insights to help designers and developers prepare for and overcome the unique challenges involved with implementation. Today’s post will focus on carrier integration.
Declining costs around cellular components have had a huge impact on how quickly the 'Internet of Things' has grown – its significance cannot be understated. Cheap components have enabled the industry to expand into countless new verticals -- it's also why providers like AT&T have turned their full attention to the M2M industry in a big way.
However, cellular connectivity brings M2M architecture and management considerations.
For one, manufacturers need to effectively and efficiently ensure that existing connected machine solutions can integrate with cellular infrastructure and mobile carrier business systems.
Here are three other things to consider:
- On A Data Budget: Manufacturers need real-time visibility into how their communications are performing against their cellular data plan, and need to be able to adjust data plans and data flow when necessary. Otherwise, they risk going over budget.
- Connectivity Management: Similarly, manufacturers need to be able to understand the status of their connectivity, and the performance and health of their assets at all times.
- Asset Management: Finding connected assets in a carrier’s system can be difficult, as the carrier’s system only identifies assets by their SIM ID. This means manufacturers often have to manually associate the asset’s SIM ID with its VIN or serial number – a long and pain-staking process.
The best solution is to leverage M2M platforms that have already achieved integration with carrier systems. This will drastically cut your time-to-market and start-up costs.
By: Bill Zujewski
This is the first post in a multi-part series, which specifically explores the challenges of dealing with wireless technology as part of an M2M (Machine-To-Machine) initiative. The series will offer insights to help designers and developers prepare for and overcome the unique challenges involved with implementation. Today’s first post will focus on “reliability”.
For obvious reasons, wireless technology will play a key role in the future of M2M. And right now, the stage is being set. Technological advances in edge devices and cellular networks have made it easier and less expensive for mobile assets to be connected, removing two significant barriers to adoption. Fact is, machines communicating via cellular, satellite, or wireless connections will be just as big of a part, if not bigger, of the Internet of Things as machines with wired connections.
But it's not all sunshine and rainbows: the unfortunate reality is that wireless communications aren’t always as dependable as wired internet connections.
That said, there are a number of steps connected product manufacturers can take early in the M2M development and implementation processes that will help ensure the level of connectivity M2M initiatives require.
1. Design an architecture that assumes and accounts for intermittent connectivity by building in intelligence that queues up data when offline to be sent out once connectivity returns.
2. Build in connectivity redundancies, so that if one kind of connectivity fails, another will take over. For example – if a moving asset loses its cellular signal, the machine can automatically switch to satellite communications. This strategy is essential for mobile assets that require continual connectivity.
3. Test your assets’ connectivity. Connect the asset, take it to a specific location, and see what the connection quality is. In the end, nothing beats real-world testing.
Even though nothing is more dependable than a wired connection, wireless M2M is opening new doors for the industry – from the shipping and fleet industries to a wide range of consumer products. Wireless connectivity is a critical part of the industry’s future – it just takes a bit more thinking and planning to make it work right.
Please join us for an Axeda webinar with Modus, "Top 5 Things to Speed Your Deployments of a Usage Based Insurance Program" on Wednesday, September 25th at 11:00 a.m. EST
There have been a few blog posts recently about what the name is of this area of technology we work in… whether they are blog posts in EE|Times, GE’s Industrial Internet, Wired’s Programmable World, or Cisco’s Internet of Everything, and even internally here at Axeda there have been some vigorous discussions about the use of “Machine” in regards to “Machine Cloud” and “M2M”.)
The discussion here has been around what really constitutes a “machine” when you have “ant-sized” computers such as the KLO2 chip as reported in the MIT Technology review in May, or does an iPhone count as a machine? For sure the systems GE talks about in the industrial internet are machines…and big ones at that! According to Wikipedia (yes I know, not the greatest source available, but bear with me) the definition is: “A tool that consists of one or more parts, and uses energy to achieve a particular goal. Machines are usually powered by mechanical, chemical, thermal, or electrical means, and are frequently motorized.” And they go on to add: “Historically, a powered tool also required moving parts to classify as a machine; however, the advent of electronics technology has led to the development of powered tools without moving parts that are considered machines.” So I guess if we don’t need moving parts, then our little ant-sized chip still does qualify as a machine, and I have to modify my prior position with some colleagues.
But to me none of these terms are instantly grokable to anyone outside of the space, and maybe that’s ok. I don’t need to know the intricate and arcane terms for brewing, but I like a beer. So does Aunt Alice need to know that her smart meter sends data back to the utility company via some form of M2M connection so that they can monitor her usage, send her off-peak incentives, or allow her to use an app on her iPhone to see exactly what she is using? Probably not, to her, it’s all just magic.
So what are some examples of connected systems that can deliver up some magic for you, and allow you to explain what IoE, IoT, M2M etc. are to your friends and family:
By monitoring consumable levels in MRI machines, operations can resupply in advance to avoid downtime. Service, sales and marketing can observe consumption over time, and deliver the right service, at the right time to avoid costly delays and patient/staff rescheduling.
Gauging the temperature of manufacturing assets warns the service team if there is a risk of overheating and lets finance know when warranty guidelines are not being upheld. (For one of our clients customers, their outsourced cleaners ran the machines out of parameter like this causing a $100,000 failure. By having the data showing when this was happening, the customer was able to pursue the cleaning company for restitution.)
Tracking wind turbine speed alerts operations when an asset is under producing, and helps research and development develop a more resilient blade.
Implementing a usage-based insurance strategy is revolutionizing the auto-insurance industry. Operations and finance teams can track speeds, idling time, parking location, distances traveled, hard stops and more, leading to decreased premiums for consumers.
So it probably doesn’t matter what you call it, but M2M allows you to fully harness the data that you can get from your machines as long as you have the innovative teams to see the possibility when they are developing the systems. A connected strategy can allow your company to make faster, smarter and more informed decisions across many departments and allow you to be more proactive with your customers.
If you have other examples that you use to describe the M2M space when you are having a cup of tea with your version of Aunt Alice, I’d love for you to post a comment below.
As promised in last week’s blog, this week I am going to take a look at how Machine-to-Machine devices are used in the healthcare industry to help keep the systems keeping us alive, stay alive themselves! If you took a look at the customer section of our website
for companies in the healthcare industry, you can see that we have a lot of companies listed that provide solutions to securely connect, manage, and innovate everything from MRI machines to blood analyzers.
These manufacturers turn to an M2M platform for many reasons, but top among them is improving the service offerings that they provide. One customer told me that a system being out of action for a single day can result in 35 patients being unable to receive treatment, so minimizing system downtime, and providing out-of-hours preventative maintenance is essential to ensuring that people receive treatment as and when they are scheduled.
Another customer provides devices to clinics to assist with IVF treatments by checking the viability of embryos. The procedure can take a day or more to run for each patient, and so the company needed to find a way to ensure the success of each treatment not only for the clinic using the system, but for the patient who had invested not only a lot of money, but also a lot of emotion into the procedure as well. So, they needed to ensure that they could be preemptive in the availability of their systems by collecting and analyzing log files and consumables data so that they can proactively dispatch field service staff prior to the next treatment commencing.
One of the benefits of access to a medical device remotely is being able to calibrate a system without having to send an engineer to site. By being able to remotely and securely connect into a device, manufacturers can provide expert assistance to lab managers to ensure systems are running within acceptable parameters. One example of this is Leica Microsystems who are using Axeda in the Leica RemoteCare service offering for their tissue processors and confocal microscopes. By proactively monitoring these systems, Leica can detect parameter deviations before problems occur. For example, as soon as the temperature drifts out of range for a tissue sample, an alarm and email are sent to both Leica and to their customer in the lab, so that adjustments can be made before losing a specimen.
The ability to conduct remote support also saves the time and expense of sending field engineers to diagnose problems as well. For example, a research institution had been experiencing system crashes of its microscopes during long-term experiments, but by being able to remotely capture and analyze the saved error logs, the remote engineer could see that the memory sizes at the time of the crash fell below 500 MB. Instead of dispatching an engineer onsite to replace a defective detector board, a service representative remotely cleaned up the PC to resolve the issue. As a result, diagnosis and repair took one hour instead of three days and saved the unnecessary expense of replacing a perfectly fine piece of hardware.
The costs of field service for these incidents are not insignificant either; a customer who focuses on radiotherapy and x-ray imaging devices estimates that they save around $2,000 for each problem that they solve remotely, ant that they have also reduced their Mean-Time-To-Repair (MTTR) by 50% while saving four hours of travel time for each call.
You may wonder how remote access is securely achieved by companies such as Leica (take a look here for news last week on the latest U.S FDA recommendations for manufacturers of healthcare systems), well Axeda agents are “firewall friendly”, meaning that communications are always HTTPS initiated by the agent, so your customers never need to have IT open ports, change firewall rules, use modems or VPNs for communication, all of which can create security risks by potentially enabling intruders to gain access to sensitive patient data.
I have a few more words to say on the healthcare subject next time, but if you would like to read more about what Leica is doing, we have a case study here that you can take a look at.
Today’s posting will focus on machine data analytics. In my previous posting on what CEOs need to know about M2M, I referenced the Axeda value curve and discussed level 3, remote service and monitoring. Today, we’ll discuss Level 4… machine usage and behavior analysis… how collecting the right machine data and using the right tools to analyze the data can drive better products and services.
In a recent survey of our customers, we discovered that 87% of our customers are storing historical machine data.
What can machine data analysis tell us?
What are the benefits of building a data mart or big data system for machine data?
Here are the top 3 business drivers we’ve seen for machine data analytics:
- Predictive Maintenance – To decrease the cost of maintaining machines and to improve up-time
- Improved Product Design – To understand end-user behavior and usage patterns to design better products and prioritize new features
- Identification of Quality Issues – To understand what’s causing down-time; To identify issues with design, embedded software, part suppliers and manufacturing processes
Let’s look at each driver starting with Predictive Maintenance. If your company has equipment that needs to be maintained by you, your partners or your customers, then there are some basic questions to ask your IT, Product Management and R&D organizations:
- What machine data can enable us to proactively service machines to drive greater uptime and shorten Mean Time Between Failure (MTBFs)?
- What sensors do we have or what sensors can we add to help us detect failures before they happen?
- What patterns in machine data readings are we seeing that are early indicators of failures?
Answers to these questions will provide Engineering, Product Management and IT the requirements for capturing the right raw data on the machine. It will help field service proactive schedule maintenance or parts replacements, rather than over servicing equipment or waiting to be reactive to failures.
Product Design can be improved with machine data. Behavior data from your machines can give you insights into how end-users are using your machines. This data can be used as input into your next generation product requirements. It can help you design a product that responds to real world use cases.
Lastly, quality issues can be identified by analyzing machine data. Today, analysis of trouble tickets and field visits can provide indicators of issues in your machines. But rather than waiting for calls and tickets to accumulate, connected machine data can be collected and analyzed to detect patterns and identify issues much sooner. The patterns observed can document normal operation and identify exception patterns. These exception patterns can be used to detect glitches in software or hardware design or correlate issues with parts suppliers.
Machines can also have issues resulting from flaws in the manufacturing process. Understanding the relationships between problems and specific batches or production runs can identify a bad batch early and streamline the recall process. It is also possible the problems are more serious and still in in the current manufacturing process. In that case, the data may trigger the need to change the current manufacturing process. Net/net... If you can understand what’s causing down-time, you can identify any flaws in the manufacturing design or process of your machines.
In my next post, we’ll continue the business case discussion and move on to level 5, integration of machine data with CRM, ERP and PLM. M2M Application Platforms of today are becoming very good at turning raw machine data into standard IT formats and web services that other systems can consume. I’ll give several examples of how machine data is working its way into our customers back office systems to improve efficiency or enable new services.
A recent article in Wired magazine talking about the Internet of Things
prompted me to think of some of the Axeda customers, and how they use connected devices. Machine-to-Machine or M2M is seen by some as new and emerging, but it has been around in some form or other for a long time, one of the earliest being during World War 2 as Identify Friend or Foe
(IFF) sensors to identify aircraft, or other vehicles as friendly (or not) and to determine their bearing and range from the interrogator.
But things have on a bit since the 1940’s, so what are people doing with M2M applications now? I’m fairly new to this whole industry, so you pundits and gurus who have been in the industry for many years (we have a lot of them here at Axeda!) may want to walk away now, and just get a cup of coffee instead… because I just want to step back for a minute before we get to a use-case, and discuss exactly what (I think) M2M means, and how it may impact your organization.
The first thing you need is of course… a thing… yep, the thing you actually want to talk to… as an example, I am going to borrow from Dr. John Barrett, Head of Academic Studies at the Nimbus Centre for Embedded Systems Research at Cork Institute of Technology, who gave a good example in a recent TED talk.
Say we have a chair, and we want to know who has been sitting on that chair. We first need to give our chair a Unique Identifier, so that we know that we are dealing with that specific chair out of all the other chairs in our universe. Then we need to connect it to the outside world, so we can add a wireless device to it, then we can add pressure sensors, so that we know when it has been sat in. And finally, we can embed some other circuitry to it, so that we are able to control it whether that is robotically controlling the seat height, or activate the wireless SIM card.
The basics hold true for any device,
But once you have this great device, already connected and managed, how are you going to innovate, what new and clever thing can you do with your device now you have remote access to it? Well, you can monitor its environment, you can use it to populate search results when you are looking for your inventory (think fleet management, food shipments etc.) or you can come up with some very cool value add for your customers that you didn’t even consider before you had a connected device. And of course, a lot of customers are still just using connected devices to perform remote service or preventative maintenance on systems, providing cost savings and improved utilization of their field repair staff.
So in this blog series, I am going to highlight some of our customers, and the way in which they use connected products. And first one up is Diebold, Incorporated, who, over their 150 years have brought together a combination of innovation, expertise and quality service to become a global leader in providing integrated self-service solutions, security systems and services.
Diebold had the challenge of implementing a remote monitoring and diagnostic capability into a new line of ATMs, to enable them to reduce field service visits and minimize system downtimes. Because of the trend to a more software-driven self-service terminal, the company sought to remotely service its ATMs over the Internet, and of course given the sensitive nature of cash-dispensing ATMs, the solution need to be both proven and secure.
By embracing a connected solution, the ATMs are enabled to deliver high-quality remote services with built-in data-capture technology. This feature carefully stores pertinent information about a device’s performance for quick access. In addition, Diebold’s remote support operators are also directly alerted when an ATM problem occurs, and can begin resolving the problem immediately by viewing a mirror image of the module. This provides a level of information that allows for an in-depth analysis of ATM status messages before a technician arrives on site. And when the technician arrives, he then has a precise knowledge about that particular machine which in-turn increases the first-time-fix ratio.
If you want to read more about what Diebold is doing, you can read the case study here. And next time, I will delve into a customer or two in the medical device environment.
In part 1 of this discussion series on what CEOs need to know about M2M, I defined the term M2M (Machine-to-Machine) and discussed the role of connected products and assets in corporate strategy. The M2M thesis for this series of articles is simple… if you remotely connect your machines, equipment and assets, you can unleash the machine data into your enterprise and unlock the value of that data. So what is the tangible value of M2M? What are the benefits? What are the hard dollars to the top line and bottom line? What are the soft dollars? At Axeda we’ve defined an M2M value curve that identifies 6 levels of maturity and organizes the major value propositions into 4 major areas:
- Remote Service (Level 3) - focuses on cutting costs from customer service and field service
- Usage Analysis ( Level 4) -focuses on predictive maintenance, driving machine up-time and improving product design
- Business System Integration (Level 5) – focuses on improving efficiency and enhancing business processes often associated with CRM, ERP and PLM systems
- Value-added Applications (Level 6) - focuses on offering complementary end-user applications with your machines and differentiate your product and improve the product experience.
For this article, we’ll cover remote service. If you’re a CEO meeting with your service organizations, here are key questions you should be asking them:
- What service operations can be done remotely?
- What machine information can we provide call center and support personnel to solve problems more quickly, shorten call times and solve cases and issues more effectively?
- What information can we provide field service people to make their customer visits more effective? How can we use machine data to shorten First Time Fix Rates (FTFRs)?
- What machine data can enable us to proactively service machines to drive greater uptime and shorten Mean Time Between Failure (MTBFs)?
Answers to these questions will provide Engineering, Product Management and IT the requirements for capturing the right raw data on the machine. It will help R&D design in the right technical solution in a collaborative way with Customer Service and IT. If you’re a CEO, it is key that you have a long term remote connectivity strategy and understand what information should be monitored, collected and remotely transferred. The savings of remote service are black and white and hard dollars. Many of Axeda’s customers have saved millions of dollars per year by increasing their service efficiency, minimizing field service visits, and reducing call times. Simple remote software upgrades and patches alone can pay for the connectivity project. Recalls are another area for savings. Many recalls are now software fixes. Enabling remote patching of software drives down the cost of those recalls.
In my next post, we’ll continue the business case discussion and move on to level 4, machine data analytics and machine usage analysis. Companies often start with remotes service, but word rapidly spreads to other organizations that the enterprise now has access to machine data and usage information. The next projects after remote service are often about usage analysis, quality analysis and predictive maintenance, typically led by Engineering and Product Management.
With all the industry buzz and vendor movement around M2M (Machine-To-Machine
), the Internet of Things, and the Industrial Internet, it’s time for CEOs to understand more about M2M, the value it may bring and how connected machines and assets can change their business
. If you’re a CEO, CTO, CIO or VP reading this, you’ve probably heard the M2M term, seen the GE brilliant machine commercials and you’re trying to figure out exactly what you should be doing with M2M and connected products.
I deal with companies, many of them manufacturers, on a weekly basis who are planning on connecting their products or already shipping machines with remote connectivity built-in. And it’s no longer just about connectivity to enable remote monitoring and remote service. There is an acceleration of focus that these companies have on shipping connected products that include new applications for end-users to better service and manage connected products. In a previous blog, I called this corporate ecosystem of connected assets the “Internet of Corporate Things”
Today, I’m starting a series of articles (blog postings) to help executives understand the value of M2M to enterprises. I will include a framework CEOs can use to include connected products in their corporate strategy and strategic initiatives. For those new to M2M, these articles can serve as a primer on the business case for investing in M2M.
Let’s start with the definition of M2M. For simplicity, think of M2M as connecting “your machines”, the first M in M2M, to “your computer systems”, the 2nd machine in M2M. If you remotely connect your machines, equipment, assets, you can then unleash the machine data into your enterprise and unlock the value of that data. The value propositions are straightforward and fall into several buckets of capabilities including remote monitoring, remote service, usage analysis, ERP/CRM integration and value-added services that differentiate your products.
M2M embraces the reality that no product or asset will be an island. All products, devices, facilities, systems, equipment, goods being delivered, processes, workflows, and people will co-exist in a connected world, interact and be interdependent. M2M systems will act like social networks, socializing machine data to foster unparalleled knowledge and collaboration. The vision is grand and we’re only in the first inning, but the time to get serious about M2M is now.
In my next post, I’ll start the business case discussion with the most obvious and tangible ROI of connecting machines. You’ll have to return to find out that that is… yes, the classic tease. But seriously, I hope I’ve sparked some interest so you’ll return to hear more. As one of the leaders in M2M software, my company Axeda owes it to the industry to share what works and what doesn’t. We owe it to the industry to clearly articulate the value of M2M and why connecting machines can be transformational. I’ll be one of the voices of M2M because I enjoy it. And of course, as CMO, I owe it to my company to get the word out and move the ball forward in our quest to be the “machine cloud” everyone looks to as their great M2M enabler.
I had the opportunity to attend my first AT&T Developer Hackathon this weekend in Las Vegas as part of the AT&T Developer Summit. If you’ve never been to a Hackathon, you can picture it as the geek’s version of the Warrior Dash or the Spartan Race. But instead of mud covered runners and obstacle courses, the hackathon contestants are caffeine infused teams of innovators building killer applications with the latest technologies including the Axeda Machine Cloud and the AT&T mobile network.
It’s amazing what these teams built in less than 24 hours. In the machine-to-machine (M2M) category there was a home security app that involved a rocket launcher, a carbon monoxide detection system that incorporated social media to alert friends nearby who can help in an emergency, and a brain wave monitor that connected to your mobile phone to route calls based on your mood or level of activity. Some were fun, some were cool, but all of them were interesting and innovative.
So, all you weekend warriors out there, next time you’re looking to unleash your inner beast, may I suggest exercising your brain rather than your legs. Not only will you be less sore on Monday, you may be a little richer. The winner of the latest Warrior Dash jumped fire and ended up covered in mud. The Best Overall winning team at the AT&T Hackathon walked away with a cool $30K. Sounds like a no brainer to me.
Jump start your hacking skills at Axeda Developer Connection and stay tuned for more information on all the winning M2M applications!
How are you Using your Machine Data?
It’s time to think big: R&D wants the right priorities. Operations wants real-time tracking of remote assets. Sales wants eyes everywhere at the customer site.
As machines get easier and less expensive to connect every year, companies are realizing that the M2M data they create can provide massive benefits beyond the service team. At Axeda Connexion 2012, we asked savvy M2M adopters about what’s next for their M2M strategies, and the answer was clear – Extend the Machine Cloud to the entire organization.
Two-thirds of the M2M innovators at Connexion said they are interested, planning, or scheduled to integrate M2M data with back-end enterprise systems, with the goal of breaking down silos and sharing valuable connected product data to business functions across their organization.
M2M metrics vary from product to product, and can impact reduced time-to-market, improved productivity, and lowered or avoided costs – the possibilities are endless. Our Machine Cloud Infographic highlights some of the processes where back-end integration can have the strongest impact.
These findings demonstrate why the M2M industry is so exciting right now. Organizations are finding ways to leverage business analytics, increase automation, transform their business, and, ultimately, deliver a superior experience for customers.