With metalworking companies across all industries facing increased demands, engineers need to rethink plant and maintenance tasks and operations. Customers are expecting greater manufacturing flexibility, more reliable, fast-turnaround product shipments and higher quality standards — all at lower costs.
To stay competitive, metalworking companies need to identify more efficient approaches to a variety of production tasks. This need for ongoing efficiency is leading metalworking companies to what some have described as the 4th industrial revolution. At the heart of this latest revolution is a greater reliance on smart, data-driven technologies.
Nowhere has data-driven technology taken a more prominent role as it has in predictive maintenance.
What is predictive maintenance?
Predictive maintenance (sometimes referred to as condition-based maintenance) is a failure inspection strategy that uses real-time data and models to predict when equipment components will wear down or malfunction so proactive corrective actions can be planned. It covers a wide array of topics, including failure prediction, failure diagnosis, recommended mitigation and suggested maintenance actions to be taken after failure.
In comparison to its predecessor strategies of reactive maintenance and preventative maintenance, predictive maintenance represents a more forward-thinking, cost-effective approach. With a reactive maintenance strategy, assets keep running until they fail. The problem is that such untimely failures result in unexpected and extended downtime and maintenance. With preventative maintenance, in contrast, problems are prevented before they occur. While this approach reduces or eliminates unplanned equipment failures and maintenance downtime can be planned, it does not allow for full utilization of an asset’s service life.
What are the benefits of predictive maintenance?
Predictive maintenance allows for planned downtime while avoiding premature maintenance so plants can get the full value from components. Predictive maintenance analyzes data gathered from numerous equipment sensors to provide a holistic view of asset health.
The concept behind predictive maintenance is not new. It has existed in some form for decades and is already a dominant strategy in many other industries. It has only been recently, however, that the technology, including the sensors, computers and software, has caught up and become affordable for more widespread use in a wide array of industries, including metalworking.
The data captured from the various connected systems and sensors provides unprecedented insights into the health and total service life of critical components, making smarter maintenance strategies possible. Artificial intelligence (AI) uses algorithms to find patterns and predict mechanical failures before they occur. Instead of simply scheduling maintenance procedures based on preset intervals, a machine learning system can analyze thousands of data points to prioritize maintenance and reduce failure risks.
Predictive maintenance remains one of the most effective approaches, to date, for equipment-maintenance scheduling. It has proven to offer significant bottom-line benefits by increasing equipment availability (productivity), reducing total maintenance costs and avoiding more costly repairs. By preventing major malfunctions, a predictive maintenance program also can help to reduce accidents in the plant to create a safer working environment.
What is monitored as part of a predictive maintenance program?
Machinery connected through an Internet of Things (IoT) platform sends continuous updates on a wide array of factors that affect long-term equipment performance. Some of the more commonly used condition monitoring techniques include:
New innovations in predictive maintenance are allowing for the monitoring of multiple factors simultaneously. For example, Parker’s SensoNODE Bluetooth-powered sensors catch performance fluctuations across a wide array of components and transmit the data through the Voice of the Machine Mobile App, which records data in real-time while also tracking historical performance.
In addition, the Parker Tracking System supports any predictive or diagnostic maintenance program.
Some metalworking plants are taking their predictive maintenance programs to new levels by adding machine-learning software. Although machine learning has been researched for years, its use in applying AI in industrial plants is now advancing more quickly.
What other technologies are making a difference in metalworking?
Automation technologies are also integral components of the 4th industrial revolution, even though metalworking has traditionally been slower than other sectors in its adoption of automated processes.
Robots and their smaller cobot counterparts have, more recently, been making their way into the metalworking industry. Now with lower costs, robots and cobots are seen as attractive solutions to counter skilled labor shortages.
Also gaining popularity are 3D printers, which have proven valuable due to their ability to manufacture more complex and lightweight parts and offer the design flexibility that’s necessary to compete in today’s highly competitive markets. Today’s 3D printers can create intricate parts directly from a CAD drawing, effectively eliminating the need for multiple lathe and mill setups. Until recently, 3D printing was almost exclusively used in the plastics industry, but it is now being adapted for metalworking.
How is technology shaping the future of the metalworking industry?
A new generation of technology is allowing metalworking plants to become more efficient and competitive.
Predictive maintenance innovations that can help reduce production downtime and contribute heartily to corporate bottom lines are key. Although many people in the industry may not think of the maintenance shop as being a prime location for investing in cutting-edge technology, the reality is that new maintenance metalworking technologies offer tremendous potential.
Article contributed by the IoT and the Fluid and Gas Handling Teams.
As the management of manufacturing plants and other assets grows more complex, integrating automated monitoring of key performance indicators (KPIs) at the discrete level provides a built-in safeguard against unplanned downtime or consequential damages.
And it addresses one of the roadblocks many have discovered with a top-down enterprise-level path to IoT: the requirement for significant investments in infrastructure around equipment and business processes, with little ROI to show for it in the near term.
A detailed analysis by Accenture and GE revealed that in the Connect-Monitor-Analyze-Predict-Optimize continuum, companies reported a higher percentage of Analyze activity than Connect and Monitor over the course of IoT’s time in their industrial space. In an increasingly connected world, these findings point to an out-of-sequence disconnect.
They suggest that efforts to understand the voluminous amount of data have come before establishing the connected infrastructure needed for data-driven decision making – and well before making a coherent business case for the data collection. In other words, the raw data available often has not been connected to the specific insights required.
The discrete IoT approach to ROI
Discrete IoT views a large machine asset as a collection of systems and subsystems with data onboard that can be given a voice with sensors, and deliver ROI in short order. Every subsystem contributes to the overall performance of an asset, and knowledge in that subsystem can be harnessed to assess its health or predict its failure. Consider which products in a motion control subsystem could provide safety, reliability and productivity insights. Pumps, actuators, valves, and filters all contain current-state performance and diagnostic data.
Having a current-state view of machine health is better than nothing, but simply publishing it on a dashboard screen stops short of being able to optimize a system or a process. The greatest power of IoT stems from the ability to perform historical analysis with time-series data, whether it be KPI-driven alerts and alarms to maintenance personnel; profiles and trend curves that pinpoint root causes of failures; or notifications to ordering systems. One primary goal is to be able to examine the conditions preceding work orders, unplanned downtime or other failures as data is correlated and presented on user-friendly interfaces that make the decision options very clear.
What is the sensor?
In motion control subsystems, pumps, actuators, valves, and filters all contain current-state data about a machine’s health that can be inspected, unlocked and sent from the equipment to a decision-maker via networked, wireless sensors. A sensor converts a physical condition such as air pressure, in-line and ambient temperature, flow or vibration into an electrical signal capable of being analyzed via the cloud or local applications for a manufacturing system.
Sensors are plugged into a machine’s existing ports or through a custom integration, and trigger alerts or alarms when tied into a control system or gateway programmed to observe when thresholds for defined performance parameters are exceeded. In this way, plant professionals can safeguard the peak performance of their operations.
With today’s wireless sensors and powerful software, it is possible to:
Notify responsible parties of an event requiring preventative or corrective action through text alerts
View real-time actionable data in graphical form from a dashboard
Export data for further analysis of historic trends to any internet-connected device
Download our Ebook, Voice of the Machine: Manufacturing's Digital Transformation for an in-depth look into how a discrete approach to the Internet of Things can lay the foundation for your company's growth.
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The ever-changing industrial Internet of Things has revolutionized the traditional landscape and business model of the construction machinery industry. Domestic and foreign parts and service providers have increased their investment and continuously launched innovative products and technical solutions based on the industrial Internet of Things.
From November 27th - 30th, 2018 Parker brought its Voice of the Machine™ industrial IoT platform to the Shanghai Bauma Exhibition. The technology covers the "last mile" of discrete IoT with a focus on interoperability, security and scalability.
In addition, Parker’s booth featured four models to fully demonstrate the powerful and comprehensive traditional hydraulic technology, covering the cab control system, chassis drive system, vehicle implement system and engine power system.
"Aligned with the new industrial landscape brought by the industrial Internet of Things, Parker created a breakthrough platform, Voice of Machine, to deliver connected products and systems. Our system integration capabilities will help address the increasingly demanding application needs of customers worldwide."
Hou Yifei, president of Parker’s Transmission and Control Group, Asia Pacific
Covering the "last mile" of the Industrial Internet of Things
At present, Internet of Things technology focuses on enterprise-level solutions, but the key component data identified and collected by the enterprise-level Internet of Things is only 10%, which greatly limits the potential of mechanical equipment to predict failures and optimize performance. Discrete IoT can deliver the remaining 90% of the core component data, which is the "last mile" that the Industrial IoT does not reach.
To this end, Parker initiated a centralized strategy to ensure that all IoT-based products and systems use the same communication standards and best practices to deliver interoperability, security, scalability and visibility.
An ecosystem of connected products and services
Through the Voice of the Machine online platform, users can interface with products, systems and professional engineers to ensure global monitoring and asset management for critical system operations.
Both IQAN® and PTS are software products based on the Voice of the Machine platform, which was also unveiled at the Shanghai Bauma Show. IQAN® Interconnect Software integrates intelligent hydraulic components and electronically controlled hardware and software to optimize device performance and simplify remote monitoring.
No matter where you are, users can use the IQAN® Interconnect Software to remotely diagnose vehicle faults and learn about current performance status through the Parker Vehicle System Gateway. IQAN® Interconnect Software provides a large number of standard function modules and a custom configuration interface. It features an adaptive web interface, which is convenient for users to view from multiple channels such as a PC, tablet or mobile phone and can easily publish data to the cloud.
The PTS Parker Tracking System is an asset management solution for critical wear components. The PTS software records detailed information about parts and assets, and users can connect to the Internet for secure access from multiple sources. The PTS generates a unique identification code printed on the barcode or RFID tag for each hose assembly.
Record and extract hose information through barcode and RFID traceability system to quickly, regularly and accurately perform equipment maintenance and repair, reducing downtime of engineering equipment. PTS can also establish an asset location database, customize inspection templates, store retrieval history inspection results, and set up scheduled maintenance reminders.
Improve system integration capabilities of traditional hydraulic technology
The EcoReach forklift assembly system is the highlight of Parker’s traditional hydraulic technology. The electric forklift is usually handled by an electro-hydraulic system. The powertrain consists of a series of separate components: an inverter that converts battery energy into alternating current; an induction motor that outputs torque and speed; and a hydraulic pump that provides flow and pressure; and a hydraulic system controls the valve block to control the flow and pressure of the required hydraulic function.
The EcoReach Forklift Assembly System integrates and optimizes these components to improve performance and efficiency, extend battery life and increase loading and unloading speed. The Parker Hannifin EcoReach Forklift Assembly system uses a fully integrated electro-hydraulic system assembly that plugs and uses to minimize the complexity of upgrading the forklift through the EcoReach system.
A large number of test results show that the system brings great potential benefits: the time to stabilize the oscillating load is reduced by 60%, the handling efficiency of the operator is improved, the time required for the entire lifting cycle is shortened, the production efficiency is increased by 13%, and the energy consumption of the entire lifting cycle is reduced by 48%. If you use the same battery to charge, the electric forklift works longer.
Learn more at Parker Voice of the Machine - Industrial IoT
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It seems like every industrial company is at some stage of planning for or deploying industrial Internet of Things (IoT) technology. According to a survey of IoT decision makers and influencers in the manufacturing, oil, and gas, and transportation industries by Bsquare for their 2017 Annual IoT Maturity Survey, 86 percent of participants had adopted IoT solutions. Almost all believed that the technology will provide a significant or tremendous impact on their industry.
Yet, while there is certainly good news on the IoT front, you can also find plenty of articles suggesting that IoT adoption is proceeding slower than many expected. A 2017 Cisco study found that 60 percent of IoT initiatives stall at the Proof of Concept stage and only 26 percent of companies considered their IoT initiatives a complete success.
The difference in those two surveys may result from who was surveyed. For their report, Bsquare surveyed “experienced, senior-level IoT decision makers” in select industries with a well-defined IoT value proposition, while the Cisco report was based on a broader survey of IT and business decision makers.
Still, there is no denying the complexity of deploying IoT broadly. It requires installing sensors or replacing legacy equipment with IoT-enabled equipment, as well as an implementation of software to support sensor management, data collection and visualization and, in some cases, machine learning. Plus, many organizations will need to address the skill gap that currently exists in the areas of IoT implementation and management.
All of that makes the move from small pilot programs, where conditions and unexpected consequences can be carefully managed, to broad deployments one of the most significant challenges we face as an industry.
Planning for scale
If you are coming off a successful pilot, you have proven the technology based on your use case and have the opportunity to build on that momentum to make a significant, positive impact on your business. Capitalizing on that opportunity starts with conducting a thorough capability and needs assessment across functional departments. Based on this assessment, you’ll need to assemble a dedicated cross-functional team to plan for and manage the deployment.
There are two factors I want to emphasize in regard to that team. First, collaboration across the business, particularly IT and OT personnel, along with engaged executive sponsorship, is crucial to a successful deployment. Second, don’t hesitate to bring in consultants and partners as needed. As the Cisco survey found, “organizations with the most successful IoT initiatives leverage ecosystem partnerships most widely. They use partners at every phase, from strategic planning to data analytics after rollout.”
One of the first questions this team must address is, what exactly does scale look like for our organization? Be clear and set expectations with executive sponsors and division leaders on what success looks like and what is required to achieve it.
This is where an IoT planning framework becomes a powerful tool. There is the experience to be gained from other adopters, but there is no off-the-shelf plan you can plug into your organization. The framework I’ve found most effective is one built around the five core components of an IoT solution. These include:
The “things” that will generate data.
How those things will be connected to the internet.
How data from those things will be collected.
Where that data will go.
Who is responsible for managing the data.
It sounds simple, but this framework can impose the necessary discipline to minimize unexpected consequences, ensure consistent collaboration and support the successful transition from limited to broad deployment.
Planning and managing the deployment
Once you have your team and framework, it’s time to begin planning the deployment. In terms of the things that will be generating data, you need to gain an understanding of their shape, operating specifications, and environmental limits. Where do sensors currently exist and where do they need to be added? For sensors that need to be added, is the most economical choice to retrofit legacy equipment or replace that equipment if it is already approaching the end of its functional life? Carefully analyzing the specific requirements of your things during the planning stage can save huge amounts of time and hassle later in the process.
The same is also true for connecting things and collecting data. This is one of the areas where collaboration between IT and OT personnel is essential. Identify exactly who from each group will be required to support the installation and commissioning and the time commitment required. Also, develop contingency plans for addressing equipment failure so you can react to those situations, if they occur, in a controlled manner that minimizes consequences.
Another important consideration is opening communication channels with on-site personnel. If they aren’t on board with the plan, the chances for success are diminished. As with any new technology, you may face resistance and skepticism, and this should be addressed early in the process.
When you’re ready to begin the deployment, the same framework used for planning can be employed. In terms of things, the challenge shifts from defining requirements to managing logistics. Who is responsible for ensuring the sensors, equipment and other technology required to support the deployment get where they are supposed to be when they are supposed to be there? The complexity of this task should not be underestimated, particularly for multi-site deployments.
This same challenge extends to the human resources required to support the “connect” and “collect” functions of the framework. Do you have the installation resources lined up, contracts in place and wiring diagrams harmonized?
Deployment is also an additional opportunity to connect with on-site resources to reinforce the why behind the new technology. Again, human factors play a key role in the success of IoT and should be addressed at every stage. Finally, take the time to practice the contingency plans you developed during the pre-deployment phase.
As you move into the post-deployment, this framework allows you to address key questions associated with system health monitoring, the integrity of data collection and internet connectivity systems and who is responsible for each, how results are reported to various stakeholders and who makes decisions about changes to the system.
Crossing the bridge
The challenge of moving from a successful pilot program to a broad deployment can be daunting and shouldn’t be undertaken lightly. But, if you have identified high-value use cases it is one that must be addressed. Developing a deployment framework that considers things, connectivity, collection, learnings and action at each stage can help impose discipline across the process and increase the likelihood of success.
This post was written by Jeff Smith, business development manager, Internet of Things.
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As a company that has produced motion and control components and subsystems in core industrial sectors for 100 years, Parker has recently taken a significant step forward by embarking on a digital transformation. Between our own journey and working with customers seeking to leverage the Industrial Internet of Things, we’ve arrived at certain truths about the process of building digital ecosystems of connected products. One of those truths is that an effective enterprise of connected “things” must have oversight and buy-in from a broad spectrum of stakeholders.
A culture of silos has no place in a digital transformation
Going digital affects too many aspects of an organization, often in ways that only become apparent later on. That’s why it makes sense to marshal perspective and talent from every corner of the enterprise when determining how best to participate in what has essentially become another Industrial Revolution.
At its most simplistic, deploying IoT effectively can achieve two things for your organization: improve your ability to save money, or improve your ability to make money. That’s the power of understanding the health of your machine assets before they break down, and carving out a market advantage based on the intelligence provided by connected devices. The decision to move into this realm requires a clear-eyed assessment of where your business is now, and where you want it to go, with input from everyone whose functional experience would or could be altered as a result of that transformation.
For example, if your responsibility is to ensure the highest level of uptime and safe operation for a fleet of off-highway work trucks or an entire manufacturing organization of factory assets, you know it would be valuable to have parts and components in that equipment enabled to alert you when service or replacement is needed. So you would want to be sure that the enterprise was selecting a parts supplier with the ability to design, manufacture, integrate and easily service such components – a partner rather than a vendor, essentially. That would involve a meaningful conversation with colleagues outside of the operations silo.
Procuring the solution is just the beginning
But what about managing the never-ending data stream created as a result of liberating the information contained within the now-intelligent parts? Can you integrate it with other databases to generate insights and drive value? What about data security and privacy? Do you have people with the right skills working for you now; can they be trained or should new talent be recruited? What about paying for all of this?
These questions and many more inform what should become part of an ongoing cross-functional conversation within the enterprise. The idea of 24/7 connectivity can be very appealing, but the key to success is having a well-thought-out strategy to tie connected products to your specific core business and deliver those solutions to the end users who can benefit from them. That only comes from having a diverse group that is well informed and connected to the process because its members fully appreciate the stake they have in it.
Our IoT roadmap to success started with customers
Our near-term IoT objective for our own OEM customers was to provide better reliability and higher performance for the components and systems they source from us (such as pumps, hoses, connectors). Built on a common platform, our IoT-empowered solutions all recognize and communicate with each other, simplifying deployment. The resulting Voice of the Machine offering makes it possible to identify what we call a serviceable event, determine the recommended next steps, and through our ebusiness capability, make it easy to remedy. That is Parker’s play in this stage of the evolution of the IoT revolution.
In our case, engaging expertise across the company when we began our journey was a nuanced process of change management. We had a lot of leaders already who had to be brought along because, while the focus in IoT may initially emphasize the “build” part of a new solution, the “operate,” “sell” and “service” elements of the solution are critical for a company like ours.
That meant engaging our head of sales, CIO, the tech office and the P&L executives closest to the customer. Providing the support they need to achieve alignment means something different to each of these functions. To deliver on the promise of true collaboration that we ascribe to at Parker, we maintained close working relationships and a high degree of transparency as we worked on what our smart product offering would ultimately look like. And it remains a living, breathing organism to this day.
So what is the digital strategy to be for your company? What current and future customer use cases should you be envisioning today to improve your customers’ experience and who in your organization should be involved in shaping those experiences? It will never be too late to get the conversation started.
To learn more about how to empower your operations with Parker’s Voice of the Machine™, visit our IoT website.
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