The Connected Effect

What CEOs Need To Know About M2M - Part 6

Posted by Bill Zujewski

Jul 24, 2013 9:37:00 AM

Part 6: Extend Machines with Connected Services to Differentiate

Today’s blog post discusses how machine data can be leveraged to deliver new applications that extend the utility of the machine for end-users. In my previous post on “what CEOs need to know about M2M”, I gave examples of business processes that have been enhanced and improved using machine data. These examples were about improving efficiency and taking out costs and demonstrated value to the machine manufacturer. As you recall, this was level 5 on the M2M value curve. But what about the end-user of the machine… how can we use the connectivity to deliver direct value to them?

The ultimate goal for product manufacturers, what we refer to as Level 6, is product differentiation. This level is about changing the product experience for customers by adding value-added apps that enhance the value of a machine. This is where connected capabilities have the capacity to transform a business and increase customer loyalty… where innovation is achieved by enabling end-users and customers to interact with the machine data… where manufacturers can reinvent their user experience.

M2M Value Cure

There are many types of custom applications that can enhance the utility of a machine. Organizations can present data from the connected product to users and end-customers via portals and web applications that they can view while using equipment in real time. For example, a web application connected to the machine may allow the user to remotely control the machine or monitor the consumables on the machine so they can to be replenished in a timely manner. The manufacturer can also provide an application to audit all machine activity and make it easy to generate compliance reports. In fact, many of our customers now provide a web portal with their equipment that provides these fore mentioned capabilities and more.  

The other big trend we are seeing is “mobile apps”. Smart phone and tablets are emerging as a way to put applications that interact with machines in the hands of field personnel and end-users who need remote access from anywhere. In some cases, workers can go home earlier knowing if something goes wrong the machine will contact them on their phone (maybe a text message) and they can quickly access the machine via their mobile device. You can see how this can reduce the labor costs for an organization while at the same time improve effectiveness of their employees.

Net/net: value-added applications can be used to improve competitiveness and drive market share. Apps can also be new revenue- generating offerings when sold as value-added services.  For the most progressive companies reaching this highest level, Axeda provides easy-to-use development tools and APIs to access collected machine data and to rapidly create new innovative customer-facing applications that differentiate their offerings. The Axeda platform also includes a rules engine and scripting engine.  Combined with the RESTful and SOAP-based web services, developers are empowered to rapidly build and deploy new applications.

In all these examples, think of Axeda as the “M2M Application Enablement Platform”… the software that collects the machine data, transforms it, stores it and then makes it easy to access and incorporate it into new applications. In my next post, I’ll share Axeda customer examples of apps that differentiate their machines and provide a competitive advantage.  You’ll see how these expanded offerings are driving rapid adoption of their connected services. Why? Because instead of trying to “sell” connected services to their customers, their customers are demanding it… their customers “need” the new applications and they fully appreciate the value that the apps can deliver to their operations and business. Just like the consumer world, in the industrial world, the notion of an “app store” for machines is emerging.

Topics: machine-to-machine, Machine Data

What CEOs Need To Know About M2M – Part 3 (How Machine Usage and Behavior Data Can Provide Business Insights)

Posted by Bill Zujewski

Jun 13, 2013 11:02:00 AM

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.   

m2m value curve level 4

In a recent survey of our customers, we discovered that 87% of our customers are storing historical machine data.  Why? 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:

  1. Predictive Maintenance – To decrease the cost of maintaining machines and to improve up-time
  2. Improved Product Design – To understand end-user behavior and usage patterns to design better products and prioritize new features
  3. 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.

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Topics: M2M, CEO, Machine Data

The Machine of the Future

Posted by Bill Zujewski

May 13, 2013 2:54:00 PM

Bill Zujewski, AxedaThere’s no doubt machines are becoming more and more sophisticated and intelligent.   During my keynote at our Connexion event last week, I discussed how machines have evolved the past few decades. Fifty years ago, machines were still mostly mechanical. It wasn’t until the past few decades that software became a major component of machines. Today, product design is just as much about software design as it is hardware design.   

Network connectivity also began to make its way into machines the past couple of decades.   Recently, we’ve seen remote connectivity being designed into the machine natively. Although the connectivity was typically put in place for diagnostics and remote service, it has enabled machine data to be used in many innovative ways including usage analytics, business system integration and new end-user apps.

So what’s next?   Here at Axeda, we’ve identified 9 major characteristics we will see in the machines of the future.  A couple of these are already in most machines… they are 1) Connected and 2) Remotely Serviceable.   Many now have GPS or some other means to locate them, making them 3) Trackable. The machine data will be available via an agent or gateway that will collect and send data and enable machines to be 4) Informative 5) Self-Healing and 6) Integrated with business systems. This machine data is also being made available via APIs enable them to be 7) App Centric. The green movement will drive machines to be 8) Eco-friendly and Energy Efficient. Lastly, machines will become part of larger systems and be 9) Collaborative.

GE calls it the Industrial Internet with brilliant machines. The Analysts often refer to it as the Internet of Things or Machine-To-Machine with intelligent systems or smart devices.  Regardless of what we label this macro trend, most agree we are in the first inning of a new “connected world” order.  The machine will be at the heart of it and I welcome the machine of the future… healthy, wise, well-spoken, green and social! Here at Axeda, we are working hard to connect these machines to Axeda’s Machine Cloud… to unleash all that machine data and unlock all the value.

Topics: Machine Cloud, Machine Data, Machine of the Future, Connexion

Enterprise Integration of Machine Data: Big-Time Value for Everyone

Posted by Bill Zujewski

Nov 7, 2012 9:11:00 AM

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.

Machine Cloud InfographicTwo-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.

Topics: M2M, machine-to-machine, CRM/ERP, Machine Data

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