5 Reasons Industrial Remote Monitoring Will Soar in 2021

Remote Monitoring

5 Reasons Industrial Remote Monitoring Will Soar in 2021


In 2020, remote operations and management emerged as a business-critical activity across industry 4.0. While the digitization of operations is already recognized as a key driver to competitive differentiation, COVID-19 concerns have increased the pressure for new levels of efficiency, productivity and safety from a distance. Companies must innovate in order to stay resilient during these challenging times which makes process improvements, improved supply chain management, and investments in information technology and automation critical. Thanks to the advancements in IoT sensor technologies and wireless connectivity, industrial organizations can make a seamless transition to remote monitoring that ensures business continuity and peak performance 24/7. With access to rich real-time and historical data of processes, assets and plant personnel, organizations can better manage production, maintenance and improve safety across multiple sites.

Here are the 5 reasons remote monitoring will soar in 2021

1. Ensure Employee Health and Safety

The pandemic has urged most organizations to transition to a remote workforce, where possible. While many jobs across industry 4.0 still require onsite presence, environmental monitoring, asset management and predictive maintenance solutions allow more of the workforce to work remotely, while maintaining the integrity of the business. Sensor data collected from assets, machinery and facilities can be used to manage equipment performance and utilization, quality assurance, inventory levels and plant operations, 24/7 from anywhere. When a failure is imminent, the monitoring system can communicate directly with service teams, ensuring an expedient repair or service process and eliminating the need for employee intervention entirely.

On the other hand, IoT applications such as remote condition monitoring, provide real-time insights into the performance parameters of machinery and can prevent impending failures or hazards that could potentially threaten the safety of onsite employees. Likewise, applications such as occupancy and presence detection can ensure safe distancing practices are met onsite and janitorial services are deployed when necessary.

2. Reduce Operating Costs

One of the biggest factors driving remote monitoring is reduced operational expenses, especially with the increasing pressure to stay afloat during the pandemic. It is estimated that industrial manufacturers incur a $50 billion cost every year due to unplanned downtime, and maintenance expenses make up 15% to 40% of total production costs. Remote condition-monitoring predicts and prevents serious equipment failures ahead of time to maximize equipment uptime while reducing maintenance costs. Moreover, remote monitoring and automatic reordering of raw materials helps prevent costly production halts caused by low supply levels. It also helps avoid excess inventory which can cause freight-in, storage and insurance costs. Labor costs are also reduced as remote operations facilitates more effective multi-site monitoring which requires fewer personnel overall.  

3. Maximize Uptime

Any time equipment is not operating during business hours, production suffers, and significant costs are incurred. Remote monitoring plays a central role in predictive maintenance practices to avoid unplanned downtime and equipment failures. IoT sensors are used to track and analyze the status, performance and stresses of critical assets like motors, pumps, and conveyers. For example, monitoring equipment vibration reveals important insights that can indicate looming failures. An unwanted increase in vibration intensity produces detrimental forces to the components which jeopardize equipment lifetime and quality. Without timely intervention, asset failures and process shutdowns are inevitable. Remote monitoring alerts personnel of potential issues in real-time so they can immediately troubleshoot issues, modify an operating parameter or provide on-site workers with instructions as to how best fix a problem or improve performance. Even when issues cannot be prevented, remote monitoring can help rapidly resolve issues that do occur, accelerating mean time to repair and first-time fix rates to ensure maximum uptime.

4. Quality Control and Assurance

Beyond reactive, end-of-run quality inspection, remote monitoring enables a proactive quality control approach to diagnose and prevent defects much earlier in the process for peak production rates and repeatability alongside reduced costs and waste. Equipment-related issues and ambient conditions can significantly impact the quality of raw materials and end products, both during production and in storage. For instance, inadequate air pressure can cause dust infiltration which can significantly impact product quality and even damage machinery and production equipment. Similarly, temperature fluctuations in processing and storage facilities can impact quality assurance and safety, especially in the food and beverage industry. Remote monitoring provides a wide range of critical machine, process and environmental data in real-time so managers can quickly identify problems and root causes for quick and remedial action such as adjustments to equipment or the HVAC system.

5. Replicate Success

For larger manufacturers with multiple plant locations, remote monitoring offers a consolidated model of performance trends across all sites. From a central location, data can be compared to identify and replicate the successes of the highest performing plants. Detailed historical information can also be compared across facilities and analyzed to identify potential problems early and enable managers to implement changes to improve efficiency, cost-effectiveness and safety.

With the future of industrial operations uncertain, organizations must remain flexible and adaptable. Investing in IoT sensor technologies and scalable wireless IoT connectivity is essential to respond to changing customer needs, better manage production changes and drive operational excellence in any condition.


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Digital Twins for Industry 4.0: Applications, Benefits, and Considerations

Digital Twins for Industry 4.0

BehrTech Blog

Digital Twins for Industry 4.0: Applications, Benefits, and Considerations

If you are a tech-savvy person, you’ve most likely heard about “Digital Twins”. Digital Twins are a major Industry 4.0 trend to watch and this week we take a closer look at this innovative technology and why Digital Twins matter to the industrial world.

Digital Twins in A Nutshell

Digital Twins have garnered significant interest over the last few years as the Internet of Things (IoT) has become more and more pervasive. A digital twin is a virtual model that mirrors a physical object or process throughout its lifecycle. Providing a near real-time bridge between the physical and digital worlds, this technology enables you to remotely monitor and control equipment and systems. Ultimately, it can execute simulation models to test and predict asset and process changes under different “what-if” scenarios. Leveraging digital twins, companies can realize substantial benefits such as improved operations, product and service innovation, and faster time-to-market.

Creating a digital twin requires different elements, including:

Sensors capturing operational behaviors of assets and processes (vibration, temperature, pressure, etc.), alongside their functioning environments (air temperature, humidity, etc.)

Communications networks providing secure and reliable data transfer from physical devices to the digital world

A digital platform that serves as a modern data repository pooling and storing shop floor sensor data with high-level business data (e.g. MES, ERP). By combining these data sources, actionable insights can be derived for data-driven decision-making – using advanced AI/machine learning algorithms.

First realized in the aerospace industry, digital twins are now gaining traction across industrial verticals. You can build a digital twin of almost everything regardless of its size – from single components and assets (rotors, turbines, pipelines, etc.) to complex processes and environments (production lines, manufacturing plants, wind farms, etc.). The level of sophistication and detail of your digital twin models depends on the availability and maturity of your IT infrastructure.

3 Applications of Digital Twins for Industry 4.0

Digital twin technology renders unprecedented visibility into assets and production to spot bottlenecks, streamline operations and innovate product development. Below are the three major applications of digital twins for Industry 4.0.

Predictive Maintenance: Gaining a holistic view of the health and performance of equipment, companies can immediately detect anomalies and deviations in its operations. Maintenance and replenishment of spare parts can be proactively planned to minimize time-to-service and avoid costly asset failures. For OEMs, predictive maintenance using Digital Twins can provide a new service-based revenue stream while helping improve product reliability.

Process Planning and Optimization: A digital footprint ingesting sensor and ERP data of a manufacturing line can comprehensively analyze important KPIs like production rates and scrap counts. This helps diagnose the root cause of any inefficiencies and throughput losses, thereby optimizing yields and reducing wastes. Taking it one step further, rich, integrated historical data on equipment, processes, and environments can enable downtime forecasting to improve production scheduling.

Product Design and Virtual Prototyping: Virtual models of in-use products provide comprehensive insights into usage patterns, degradation point, workload capacity, incurring defects, etc. By better understanding a product’s characteristics and failure modes, designers and developers can correctly evaluate product usability and improve future component design. Similarly, OEMs can deliver customized offerings for different groups of customers based on specific usage behaviors and product implementation contexts. Digital twin technology additionally aids in developing virtual prototypes and running robust simulations for feature testing based on empirical data.

Real-world Use Cases

Digital Twins for Industry 4.0

Key Considerations for Deploying Digital Twins

Analysts like Gartner have advocated for a soon-to-be digital twin explosion, predicting that half of all large manufacturers will have at least one digital twin initiative by 2020. Beyond the hype, it is important that companies accurately assess their readiness for undertaking the complexity of such an initiative. It boils down to how data – the lifeblood of digital twins – can be aggregated and put into use.

In legacy automation and control systems with proprietary industrial protocols, sensor data are encapsulated in local, closed-loop processes and not exchangeable externally. Retrofitting brownfield with IoT connectivity to break down these silos and make valuable data accessible across the company, can be a daunting process. What’s more, connecting mobile industrial vehicles and remote, hard-to-access equipment will require a different type of connectivity that satisfies special requirements like mobility support and range. Therefore, prior to starting a digital twin project, companies should consider whether a sufficient communications infrastructure is already in place for effective data collection.

Even with enough data at hand, structuring and analyzing these data to create values will be another hurdle to overcome. To avoid overcomplexity, it is important to assess your existing digital capability from the outset and determine the optimal level of digital twin model details accordingly. Similarly, a balanced approach to retaining software, simulation, and analytics resources is required.

Final Thoughts

The best way to embark on a Digital Twins initiative is to identify the asset(s) and process(es) with the highest potential for value creation, and then begin a pilot implementation. A digital twin should be a work-in-progress that continuously evolves and scales – as your IT capacity expands and matures. Typically, digital twins of various single components can later be interconnected to form a large, composite twin of a highly complex machine or process. Also, recursively monitoring and measuring created values over time will provide a better idea where the most tangible benefits can be realized.

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5 Industrial IoT (IIoT) Predictions for 2019

IIoT Predictions for 2019

BehrTech Blog

5 IIoT Predictions for 2019


We are in the midst of digital transformation and the industry 4.0 revolution. From manufacturing and mining to oil and gas and utilities, more companies are adopting the Internet of Things for its obvious business benefits. Accenture estimates the Industrial Internet of Things (IIoT) could add $14.2 trillion to the global economy by 2030.

Industrial IoT solutions continue to prove their immense value; allowing for an easier, and more efficient and affordable way to manage processes.

As the Industrial IoT landscape rapidly evolves, what can we expect in the coming year? Here are our 5 IIoT predictions for 2019.

[bctt tweet=”Embracing upcoming IIoT trends as part of your next digital strategy is key to driving continuous innovation and staying above the competition.”]

1. LPWAN Helps Break Down Industrial Data Silos

Legacy industrial systems often run on disparate, proprietary communication networks that don’t enable data exchange. In addition, many industrial campuses are located in remote areas with extremely difficult terrains and topography, alongside heavy physical obstructions. This makes traditional wired and wireless solutions like cellular or short-range technologies too complex, expensive and unreliable to implement; leaving industrial companies with huge amounts of isolated and inaccessible data acquisition points.

Predicted to support 3 billion IoT connections by 2025, Low-Power Wide Area Networks (LPWANs) are a new wireless phenomenon promising to combat these brownfield challenges. With its long range, deep penetration, and ultra-low power consumption, LPWAN brings reliable connectivity to previously infeasible industrial locations. As a cost-effective, easy to deploy and manage solution, these networks can be retrofitted in large-scale brownfield facilities to IoT-enable legacy asset and systems.

“Wireless connectivity that was previously too expensive to implement or not technically feasible to be deployed is now possible,” emphasizes Michel Hepp, BehrTech’s VP of Global Sales. “We now have viable communications solutions that can connect these previous ‘islands of data’ to the enterprise.”

There are numerous technologies that currently fall under the LPWAN umbrella. To seamlessly support ever-growing data traffic in 2019, a robust and scalable solution with strong interference immunity will be the focus.

2. Interoperability Gives Rise to Turnkey IoT Solutions

Interoperability of Industrial IoT devices will be critical for the progress of IIoT ecosystems. McKinsey & Company predicted that IoT interoperability is required to create 40 percent of the potential value of the Internet of Things.

IoT interoperability is the ability for systems or elements of systems to interact and harmoniously function with each other, regardless of their manufacturer or technical specifications. For example, a communication protocol should be compatible with any commercial, off-the-shelf hardware like transceivers and gateways. It should also be able to interface and exchange data with cross-vendor cloud platforms for data storage and analytics.

IoT is inherently an ecosystem game where no single technology alone can provide a complete solution. Interoperability, fueled by open, industry-standard technologies, will enable a new wave of turnkey solutions delivered by IoT vendors and system integrators. By bringing different components of the IoT value chain together, these out-of-the-box offerings help customers streamline complexity and accelerate ROIs.

As BehrTech’s Chief Product Officer, Wolfgang Thieme highlights, “since IoT involves so many technologies from the sensor through the network to the cloud, there is a critical need for end-to-end solutions. It is difficult for end customers to adopt and integrate everything themselves. Therefore, a strong partner ecosystem is key for successful IoT connectivity and solutions.”

3. End-to-End Communications Security Becomes A Norm

Reducing security vulnerabilities will remain a primary focus. With the rising number of IoT devices, hackers and cybercriminals are continuously finding new ways to compromise IoT devices and networks.

In the 2019 fight against cybercrime, multi-layered, end-to-end security throughout the IoT data chain – from end nodes to the gateway to the Internet and finally end users’ application platforms – will be imperative. Advanced Encryption Standard (AES) can be paired with Transport Layer Security (TLS) protocol to enable such a versatile end-to-end security. AES is an open encryption standard widely employed for data link layer encryption in low-power IoT networks, while TLS is an application-layer cryptographic protocol for secure web communications. Adoption of these industry-standard, well-proven solutions is crucial to protect the integrity and confidentiality of IoT data against imminent cyber-threats.

What’s more, securing IoT devices will become more complex due to the diversity of control platforms. To overcome such complexity, Microsoft released a list of security best-practices for IoT devices:

Hardware-Based Root of Trust: To make IoT devices hardware-secure against attackers a single-purpose hardware should be used as well as built-in features to detect a hardware attack.

Small Trusted Computing Base: By only using a small trusting computing base and minimizing the hardware and software, failures will be reduced.

Defense in Depth: When using multiple security layers, the device will still be secure even when an attacker manages to remove one layer because other measures can still prevent intrusion.

Compartmentalization: By separating hardware and software an attacker doesn’t automatically gain access to all other parts of the device when he has hacked one of them.

Certificate-Based Authentication: Certificate-based authentication is recommended since it can’t be forged like a password-base authentication.

Renewable Security: Renewing the security with regular updates will help to approach new threats and vulnerabilities.

Failure Reporting: With built-in and automated failure reporting, attempted attacks can be analyzed and used to improve security.

4. Edge Computing Goes Mainstream

According to TechRepublic, by 2020, data traffic generated by smart sensors and other IoT devices will reach 507.5 zettabyte. Managing and analyzing this huge amount of data will be a significant challenge for organizations as cloud computing remains under pressure to meet the data computing and intelligent service demands of IoT devices and applications.

That is why edge computing is gaining more popularity. Instead of data management and analysis being performed at big cloud and enterprise data centres, it is generated, collected and analyzed close to the data source i.e. IoT sensors and devices. This reduces the latency between devices and the data processing layer to allow data to be delivered in real-time. Edge computing also enhances compliance and security as data is stored locally, giving hackers fewer opportunities to access all data at once.

As IoT deployments expand in 2019, more companies will look to build infrastructures that can handle this massive amount of critical data. Edge computing provides the reliability and security needed to make intelligent decisions in real-time.

5. Digital Twin Advances Operational Excellence

Another innovation expected to revolutionize Industrial IoT are Digital Twins.

A Digital Twin is a near real-time virtual representation of a physical object or process built to optimize business performance. By creating a complete digital footprint of critical assets, the digital twin enables industries to detect physical issues more quickly, predict outcomes more accurately, and design and build better products, systems, and processes.

For example, manufacturers can use digital twins to create a virtual representation of a field asset. Then as data is captured from smart sensors embedded in the asset it provides visibility into real-world performance and operating conditions. Manufacturers can also simulate that real-world environment for predictive maintenance.

McKinsey predicts linking the physical and digital worlds could generate 11.1 trillion a year in economic value by 2025, while Gartner predicts that roughly half of all large industrial companies will be using digital twins by 2021. As more industries focus on reducing operating costs and extending the life of equipment, we will certainly see a spike in Digital Twin applications and uses cases in 2019.

Today, digital transformation is no more a choice, but a must for industrial companies to secure their competitive edge. Beyond the hype, IIoT is getting closer to reality with increasing maturity and adoption of sensor, networking and analytics technologies. Embracing upcoming IIoT trends as part of your next digital strategy is key to driving continuous innovation process and stay on top of the competition in 2019.


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