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Evoorts Solutions provide digital manufacturing Industrial IOT Solutions and IIOT Development Services to improve your business and ROI. Contact us now.
Digital transformation is disrupting businesses in every industry by breaking down barriers between digital and physical worlds. Take control of your data and then utilize it wisely. Move computing to your digital data to save decision time while eliminating the cost and danger of transmitting information to the cloud. Discover correlations in your data to establish causality, correlations, trends or hidden patterns , and maximize productivity and predictability.
Our Industry 4.0 solution helps manufacturers to link multiple production lines and devices, collect data from multiple different sources at different production points, and build technologies such as remote monitoring, edge analytics, predictive maintenance, and virtual twins.
We provide strategic consultancy to assist clients in developing a long-term strategy before commencing a digital journey. This comprises maturity evaluation, identifying digital opportunities, and developing a technology and execution strategy.
https://www.evoortsolutions.com/services/digital-manufacturing-industrial-iot
Business Process Automation (BPA) helps to perform repetitive, mundane, tasks, freeing human capital to focus on more complex, creative and less repetitive tasks.
Evoort’s BPA platform enables enterprise-wide planning and execution of the software, combining silo processes, systems, and data developing internal adaption and scale capacities, and more importantly, creating business value and competition.
ZTNA stands for "Zero Trust Network Access." It is a security model in which access to network resources is granted based on the principle of "never trust, always verify." In a ZTNA system, all network traffic is treated as untrusted and is subject to authentication and authorization checks before being allowed to pass. This approach helps to prevent unauthorized access to resources and mitigate the risk of cyber-attacks.
Why Is Interest in ZTNA Growing?
Interest in ZTNA is growing for a few reasons. One of the main reasons is the shift to remote work and the use of cloud-based services, which has made traditional network perimeter security less effective. With employees accessing corporate resources from a variety of locations and devices, it has become more difficult to protect the network from unauthorized access.
Another reason is the increasing number and sophistication of cyber-attacks. As cybercriminals become more advanced in their methods, traditional security measures such as firewalls and VPNs are no longer sufficient to protect against all types of threats.
ZTNA provides a more comprehensive security model that can help organizations to better protect their resources and data, even in a remote and dynamic environment. It also allows IT teams to have better control of the access and activity of the devices and users on the network.
Additionally, compliance regulations like HIPAA and PCI-DSS are requiring more secure access and management of sensitive data, and ZTNA can help organizations to meet those requirements.
What is the mechanism of ZTNA?
Permission to specific applications or resources is given only when the user is authenticated to the ZTNA service when using ZTNA. Once authenticated, the ZTNA provides the user access to the particular application via a secure, encrypted tunnel, which provides an additional layer of security by covering apps and services from IP addresses that would normally be visible.
ZTNAs function similarly to software defined perimeters (SDPs), depending on the same 'dark cloud' concept to protect users from gaining access to any other apps and services they are not authorized to access. This also protects against lateral attacks, because even if an intruder gets access, they would be unable to scan the system.
ZTNA Use Cases:
Authentication and Authorization - The primary application of ZTNA is to offer a granular authorization function based on the identity of the user. Whereas IP-based VPN access provides broad network access once authorized, ZTNA provides restricted, granular access to specific resources and services. With location- or device-specific access control policies, ZTNA can provide higher levels of protection by avoiding malicious or compromised devices from using the organization's resources. This access differs from some VPNs, which grant staff devices the same access privileges as on-premises administrators.
Control and Visibility Holistically- Because ZTNA doesn't inspect traffic data after verification, there may be a problem if a malicious employee misuses their access, or if a user's credentials are lost or stolen. An organization can benefit from the security, scalability, and network capabilities required for secure remote access by incorporating ZTNA into a secure access service edge (SASE) solution, as well as post-connection monitoring to prevent data loss, malicious action, or compromised user credentials.
Journey to the Cloud- Apps are migrating away from on-premises servers and toward private and public cloud environments. IT has full control over where all these connect with a ZTNA access proxy in location. Apps can be moved to the cloud, between clouds, and back to campus with no disruption to user experience.
Benefits
Versatile Deployment: Allows ZTNA regulations to be imposed for both virtual and on-campus employees.
Granular Access Control: Specific application access is granted to that particular session.
Ongoing Verification: Before actually allowing permission to use an application, it authenticates the identity of the user, the device's identity, the device's posture, and the user's permission to use an application.
Client-Initiated Model: Gives the IT group more control and insight over the end-point while giving the user a quicker, easier experience.
Business leadership seeks to reduce overhead expenses by reducing the headcount of technical support employees at their production plant(s), while also increasing operational efficiency. This appears to be a contradiction. Is it feasible? Certainly. Because once the plant's on-site engineering support workforce has been reduced to a skeleton crew, management should seriously consider augmenting the lean production support mechanism to maintain optimum operational effectiveness and deliver output targets. Plant managers and techs have a lot on their plates: not only are they in charge of ensuring that day-to-day process runs smoothly but they are also entrusted with increasing output and income. Plant managers cannot be always around. But, in many aspects, they must be. Manufacturing plants nowadays are more efficient than ever before, frequently working continuously.
That means someone must always keep an eye on them, including while they are at their child's evening sporting event, when they are holidaying on the weekend, and even when they are asleep. Many manufacturers are finding it challenging to employ professionals in the numbers and skill sets required due to the industrial skills gap. Some organizations simply do not have access to qualified specialists within their businesses. Fortunately, there is assistance available for plant managers that offers important knowledge, backup, and support — whenever required.
Remote Assistance includes the opportunity to:
- Improve customer experience by accelerating manufacturing with fewer throughput dips.
- Remote interaction and advice can help you optimize the precision and reliability of your work.
- Increase judgment call speed by having plant personnel showcase planned work in real-time, allowing distant stakeholders to rapidly comprehend, agree on, and approve the job.
- Increase the frequency of inspections as well as the documentation of work and inspections for auditing and compliance.
- Improve employee health and safety by eliminating travel and minimizing physical contact.
- Hands-on completion of task work with remote expert help augmented by mixed reality 3D annotations, including real-time or recorded observation for future training purposes, improves knowledge acquisition, retention, and sharing.
Assure that end-user investment and ROI are maximized by utilizing connection, https://www.evoortsolutions.com/blog/reducing-customer-unplanned-downtime-to-boost-business-value-and-operational-revenue, and predictive maintenance to avoid expensive customer downtime and provide more reliable operations. Learn how to use augmented reality-based remote help to swiftly extend problem-solving advice, assistance, and expertise to your manufacturing operations and service teams. With powerful AR collaboration capabilities and real-time video communications, a field technician may simply connect with a specialist to observe and evaluate the scenario at hand. Utilize the devices currently in your workers’ pockets to improve remote support and speed AR’s time to value in your organization.
Reasons for Unscheduled Downtime:
- Human error is one of the biggest causes of downtime in the sector, which is not unexpected given the growing number of hyper specialized machinery and equipment that demand the upkeep and supervision of maintenance professionals and specialists.
- The second problem identified is a lack of information about the status of the equipment. In reality, businesses do not know the actual status of their equipment or when it should be maintained, improved, or replaced.
Allow for professional advice at any time and from any location. Utilizing today's handheld apps, Evoort assists industrial businesses in swiftly scaling the expertise of service specialists and operations professionals. REDUCE COSTLY TIME ON SITE: Fix, repair, and solve troubles extra quick via way of means of allowing frontline people with real-time AR to guide out of your maximum skilled crew members. Eliminate useless tour expenses and expenses related to repeat visits ENHANCE UPTIME AND EFFICIENCY: Lower downtime and speed issue resolution by linking your field employees and customers with specialists who can advise and coach them through the troubleshooting and repair procedures. IMPROVE SAFETY AND COMPLIANCE: Keep service technicians secure while maintaining dangerous equipment and work situations by allowing specialists to mark up a technician's real-time view with callouts highlighting precise information, risks, or procedures to take to avoid mistakes and mishaps. PERMIT CUSTOMER SELF-SERVICE: Minimize client downtime by allowing them to fix on-site challenges on their own. Engage your consumers with the skilled assistance they require to quickly diagnose and fix issues.
In 2023, a total of 41.76 billion IoT or Internet of
Things-connected devices are anticipated to be deployed, per ReportLinker. As
per Guidehouse Insights’ estimations, The global market for IoT in
manufacturing is set to grow to $23.1 billion by 2031, growing at a compound
annual growth rate (CAGR) of 15.0%. Industry 4.0 is here, set to boost
competitiveness across companies.
A McKinsey research reveals IoT is poised to deliver $1.3
trillion in economic value to the manufacturing sector. Among these also is
standardized production settings, but requiring scale for ensuring thorough
capture.
McKinsey research also states IoT’s potential global
economic value to unlock by 2030 could be $5.5 trillion to $12.6 trillion. But
barriers exist, in the form of machinery upgrade costs, investment optimality,
and cybersecurity
risks.
The ultimate Industrial Internet of Things or IIoT
applicability lies in the manufacturing sector. Production lines and industrial
machines’ productivity could massively boost with internet connectivity and
sensors, monitoring production. These could include monitoring temperature,
humidity, noise, or vibrations.
Let’s examine the various IIoT trends in manufacturing:
Transforming IoT Business Model
Industrial IoT Solutions are appealing as they enhance
factory performance via augmented output, whilst also bettering key business
metrics. IoT is an automation catalyst, allowing manufacturers to transform
business models with innovation. The approaches on which IoT works include
the product, the supply chain, and the manufacturing. Championing these three
aspects would enable charting a crystal-clear smart IoT adoption strategy.
Predictive Maintenance & Performance Tracking
Big enterprises have heavily invested in their IoT and IIoT
infrastructures in 2022. In 2023, much attention would be directed toward
predictive maintenance and performance tracking in products and plants.
In today’s advanced industrial environment, factories are
even looking forward to lights-out manufacturing (total automation). IIoT
solutions and deep analytics software today can enable end-to-end production
processes’ performance tracking by manufacturers. Novel machine learning (ML)
technologies have facilitated predictive performance tracking capabilities via
sensor-collected big data analyses.
ML can also facilitate performance tracking to get better
with time, enabling industries to operate for sustained periods without human
oversight.
Equipment downtimes in production environments result in
out-of-the-blue delays and subsequent losses. So, smart operational schedules
are a must for efficient execution and asset availability. That’s when
predictive maintenance can considerably decrease machine failures and power
outages, boosting overall asset life.
Use predictive maintenance to enhance asset life-cycle,
reduce maintenance costs and time, and decrease machine breakdown to enhance
equipment monetization It also allows a reduction in accidental malfunction to
strengthen workers’ physical safety.
Augmented Reality (AR) and Virtual Reality (VR)
AR (Augmented Reality) and VR (Virtual Reality) can be
accessed to experience immersive training, remote
assistance, and collaboration. Instruction manuals’ digitization via AR and
VR is the next frontier in redefining industrial technologies.
Capitalizing on the prospects presented by data exploration,
Virtual and Augmented Reality can minimize waste in industrial processes. VR
and AR can be easily integrated with IoT. Together these technologies can reap
tremendous benefits. Such breakthroughs can come in the form of higher profits,
exploring fresh growth avenues via new products or services, decreased costs,
etc.
AR acts as an enhancement of the user’s surroundings via the
addition of digital components in a live environment. VR replaces real-life
environments with simulated ones as the user is completely immersed in a digital
environment. In the manufacturing sector, VR and AR can be leveraged to make
available designs, organize manufacturing lines, sharpen ideas, and remote
machinery interaction. If in the building process either of the steps is
omitted, its identification is possible via AR and VR.
AR and VR can be integrated in these ways with IoT:
Asset Management: Equipment know-how, performance, and health
data are collected via IoT sensors to transform these into their virtual form.
By doing so, real-time visualization of breakdowns and crashes is possible.
Space Management: The AR technology optimizes inventories in
factories or warehouses, developing optimal routes for workers to navigate
across facilities.
Employee Training: AR allows manufacturers to develop
virtual prototypes of products for integration with IoT data. By doing so, it
can develop a simulation wherein your employees can learn machines’ optimal
usage.
AR and VR can guide technical work by offering real-time
instructions. These technologies can also facilitate technical support on a
remote basis, making training experiences real. AR can analyze machine
environments’ problems. Computer vision in AR can give a map of machines,
allowing highly-skilled laborers to witness real-time manufacturing processes’
stats.
Big Data Insights to Boost Optimization
IoT technology essentially collects data. Industrial Big
Data, for that matter, is a central aspect of Industry 4.0. A smart factory
operates at its optimal level owing to an accurate collection and the finest
analyses of data. There are also several challenges presented by Big data, such
as the efficient collection of the required data (via IoT analytics) and
attributing to it enough value (via integrating artificial intelligence). The
availability of Big Data can make available deeper insights. Unlike traditional
technologies, a multitude of production or supply chain aspects can be tracked
via IoT devices. So, IoT is crucial from the Big Data and manufacturing
perspective.
Edge Computing
The edge computing trend is eagerly looked forward to by the
manufacturing industry as an enabler of automation implementation in factories
and supply chain processes. Edge computing can enhance manufacturing processes
via advanced robotics and machine-to-machine communication. Edge computing
essentially involves various networks and devices surrounding the user to
process data as near to its area of generation as possible at high speeds and
volumes. The outcome of this is a result-oriented action plan in real-time. In
manufacturing, via edge computing, several local edge network factory devices
can enable processing with no need to send data (to a local server first). Edge
computing is speedy, highly efficient, and indeed secure.
There is no need in edge computing for the sensitive
manufacturing data to leave (for distant server processing) the factory
premises. So, there is a reduced risk of hiccups or third-party intrusion.
Enterprises of today can boost their business prospects via the integration of
edge computing and AI, to develop Edge AI.
This way, edge computing facilitates undertaking AI
computation close to the user at the onset of the IoT network, instead of on a
cloud. So, enterprises can attain real-time intelligence in industrial
operations, strengthen privacy and cybersecurity, contain costs, and better
manufacturing processes.
Conclusion
Manufacturing industry solutions based on IIoT are poised
for stupendous growth with efficient asset
management and monitoring, predictive maintenance for reduced machine
breakdown (via performance tracking), and boosted workplace safety.
Entrepreneurs can look forward to profitable business with IIoT transforming
business models.
The future of enterprises is digital. Transformation is the way forward for manufacturing. A smarter, speedier, seamless, and safer production environment is next. Digital transformation is paving the hyper-automation pathway for improving efficiency.
Advanced wireless networks are set to be used to reduce downtime as the Industrial IoT (Internet of Things) gets deployed everywhere. As the production landscape is in a constant state of evolution, it’s vital to clearly decipher what digital transformation actually means.
Digital transformation primarily integrates digital technology across various areas of a business. The objective is to considerably alter the manner of operation, for delivering value to customers. Digital transformation digitizes non-digital services, operations, and products. The underlying intention is to elevate value via invention, innovation, and efficiency.
Factories and processing plants globally are embracing automation for enhanced production, efficiency, and quality.
But the future automation platforms would offer vital smart insights for real-time operational efficiency. These timely recommendations might include, for instance, machine learning-powered automation in decision-making.
Industrial Internet of Things (IIoT) technologies, cloud and edge software, machine learning (ML), artificial intelligence (AI), and low-code platforms are poised to facilitate advanced automation. Together such an apparatus would enable companies to march towards reaping the advantages of implementing artificial intelligence of things (AIoT).
With manufacturing entering the digital phase, a stark momentum is apparent in customer expectations and technological advancements.
Companies can expect to boost efficiency, use data optimally, make innovation conducive, and control cost with digital transformation. What are the buzzing trends in digitally transforming the manufacturing sector? Let’s examine the 5 (manufacturing) digital transformation trends in 2023.
- Industrial IoT
IIoT is a futuristic system to keep your business’ manufacturing lifecycle up and ready. Industrial IoT transforms processes for improving efficiency, whilst meeting the Industry 4.0 standards. In IIoT, smart sensors tend to enhance manufacturing operations. In an IIoT setting, Informed business decisions are swiftly reached at, courtesy of the intelligent devices and real-time analytics.
The idea is to boost internal processes’ cost-efficiency, whilst providing increased value to customers. An IIoT solution works in tandem with cloud computing and AI-based technology stack for robust manufacturing.
The utilization of such smartly connected devices can be done in the fields and factories, or at remote facilities. Look forward to automating core factory operations via applying IIoT solutions to deploy digital transformation. It tends to solve such pressing challenges as productivity, asset utilization, quality, and process automation.
An IIoT network of servers and devices tends to manage manufacturing and machinery lifecycles. It also collects, stores, and analyzes the data from the sensors, executes commands given remotely, develops smart alerts rules. Based on these, smart and actionable insights are prepared to streamline industrial systems, efficiency, and predictive maintenance. Refer to the generated trends monitoring and historical analysis reports, for predictive maintenance.
- Predictive Maintenance
Predictive maintenance is a prominent Industrial IoT trend, given its benefitting potential for the manufacturing sector. Predictive maintenance based on IIoT tends to utilize real-time data that analyzes the assets’ condition on an ongoing basis.
The benefits of predictive maintenance are an increased asset lifecycle, reduced maintenance costs, increased time efficiency, reduced machine breakdown boosting equipment ROI, a drop in unexpected malfunctions leading to better workers’ safety.
IIoT data lets companies use analytics tools to access insights. With it, companies use data visualization to assess the ongoing and predict the future performance challenges.
- Artificial Intelligence and Machine Learning
The integration of Artificial Intelligence and Machine Learning facilitates harnessing manufacturing data. These technologies’ assimilation in the service infrastructure and applications expedites the processing of data, thereby improving efficiency.
AI and ML-led digital transformation is boosting industrial robustness with operational streamlining via automation. Companies are actively investing in technologies that process massive data volumes in real-time and with accuracy.
Processing tons of data strengthens manufacturers to swiftly process and develop products while reducing costs and industrial waste.
- 3D Printing
3D Printing works towards developing products via digital data, wherein lasers work on materials’ coatings. Manufacturers can build prototypes with 3D Printing and troubleshoot errors to ensure seamless production at scale.
The not-so-affordable task of tooling is no more a necessity now with 3D Printing. Also, there is no need for physical prototypes.
3D Printing sharpens the competitive edge whilst giving constant feedback throughout the product launch pipeline. Making design solutions even more immersive, the intended users can get an actual feel of the product prior to actual manufacturing.
3D Printing enables mass customization and paves way for new geometries.
- Augmented Reality (AR) and Virtual Reality (VR)
Enabling the digitization of instruction manuals, AR and VR are poised to redefine mainstream industrial technologies in years to come. AR and VR can be leveraged to offer immersive training, remote assistance, and collaboration.
Together AR and VR can instruct on technical work via offering real-time instructions. These technologies can also facilitate technical support on a remote basis, and inject life in training experiences.
AR can analyze machine environments’ complications. Via computer vision, AR can give a map of machines (similar to a real-time visual manual). As a result, highly-skilled labor service turns into a “downloadable” skill. Workers can see real-time stats of the manufacturing process, with AR, to attain precision.
VR is a critical manufacturing process component applicable in technical training, remote equipment servicing, and reviews of designs.
Customized, modular, automated, and efficient are the words that describe manufacturing of the future. Industrial evolution is a pressing need that provides robust potential of boosting the returns on investment. With robotics, AI, and IoT digitization in place, data insights and smart robotics investments would boost output and lessen cost.
Asset efficiency, less machine breakdowns, and higher workplace safety would transform business models with digital transformation of manufacturing.
