The manufacturing industry is undergoing a massive digital transformation. Smart factories now rely on Programmable Logic Controllers (PLCs), SCADA systems, Distributed Control Systems (DCS), Industrial Internet of Things (IIoT) devices, cloud platforms, AI, and connected industrial networks to improve efficiency, productivity, and operational visibility.
While these technologies enable real-time monitoring and automation, they also expand the cyber attack surface. A single compromised PLC, unsecured IIoT sensor, or vulnerable SCADA server can disrupt entire production lines, damage equipment, or halt operations.
This is why manufacturers are shifting their focus from traditional cybersecurity to industrial cyber resilience, an approach that not only prevents attacks but also ensures operations continue safely during and after a cyber incident.
What Is Industrial Cyber Resilience?
Cyber resilience is the ability of an organization to anticipate, withstand, respond to, recover from, and continuously adapt to cyber threats while maintaining critical operations.
Traditional cybersecurity is primarily designed to prevent cyberattacks, whereas industrial cyber resilience goes a step further by preparing organizations to anticipate, withstand, respond to, and recover from cyber incidents. It enables manufacturers to identify threats early, minimize production disruptions, and restore operations with minimal downtime.
For manufacturers, cyber resilience means:
Protecting production assets
Ensuring operational continuity
Reducing downtime
Safeguarding intellectual property
Maintaining worker safety
Meeting industry compliance requirements
In connected manufacturing, resilience is just as important as prevention because even a short production outage can result in significant financial losses.
Understanding the Connected Manufacturing Ecosystem
Modern industrial environments consist of several interconnected systems that must work together securely.
PLC (Programmable Logic Controller)
PLCs control industrial machines by executing programmed logic for motors, conveyors, robotic arms, pumps, and manufacturing equipment.
Because PLCs directly control physical processes, compromising one can lead to production downtime, equipment damage, or unsafe operating conditions.
Supervisory Control and Data Acquisition (SCADA) systems collect real-time operational data from industrial assets and allow operators to monitor and control processes from centralized control rooms.
Strong SCADA Cybersecurity practices include:
Secure remote access
Network segmentation
Multi-factor authentication
Continuous monitoring
Patch management
Secure communication protocols
Without proper protection, attackers may manipulate industrial processes or disrupt production.
Distributed Control Systems (DCS)
DCS platforms manage complex industrial processes commonly found in:
Chemical plants
Oil & gas facilities
Power generation
Pharmaceutical manufacturing
Food processing
Since DCS environments control continuous operations, cyber incidents can have serious operational and safety consequences.
IIoT Devices
The Industrial Internet of Things connects sensors, gateways, cameras, smart meters, and industrial equipment to collect operational data for predictive maintenance, quality monitoring, and analytics.
Today’s manufacturing environments face increasingly sophisticated cyber threats.
Some of the most common include:
Ransomware: Attackers encrypt production systems, preventing normal manufacturing operations until a ransom is paid.
PLC Manipulation: Unauthorized changes to PLC logic can alter machine behavior, reduce product quality, or damage equipment.
Supply Chain Attacks: Compromised software updates or third-party vendors may provide attackers access to industrial environments.
Insider Threats: Employees or contractors with excessive privileges may intentionally or accidentally expose critical systems.
Remote Access Exploitation: Poorly secured VPNs and remote maintenance tools remain frequent entry points into industrial networks.
IIoT Device Exploitation: Default passwords, outdated firmware, and unsecured industrial sensors provide attackers with additional attack vectors.
Cybersecurity vs. Cyber Resilience
Traditional industrial cybersecurity focuses on preventing cyberattacks through firewalls, antivirus software, access controls, and network protection.
Cyber resilience goes further by preparing organizations to continue operating even when attacks occur.
A resilient manufacturing environment can:
Detect threats quickly
Isolate affected systems
Continue critical operations
Recover rapidly
Learn from incidents
Improve future defenses
This proactive approach significantly reduces operational and financial risks.
Best Practices for Industrial Cyber Resilience
1. Secure PLC Infrastructure
Strong PLC security starts with understanding every controller deployed across the facility.
Recommended practices include:
Disable unused ports and services
Apply firmware updates where possible
Use strong authentication
Restrict programming access
Monitor configuration changes
Back up PLC logic regularly
2. Strengthen SCADA Security
Modern SCADA Cybersecurity requires layered protection.
Organizations should:
Segment SCADA networks
Encrypt industrial communications
Limit remote access
Monitor network traffic
Enable role-based access control
Maintain detailed audit logs
3. Protect IIoT Devices
Every connected sensor increases the attack surface.
Manufacturers should:
Maintain complete IIoT asset inventories
Replace default credentials
Encrypt device communications
Regularly update firmware
Monitor device health
Remove unauthorized devices
4. Segment IT and OT Networks
Flat industrial networks allow attackers to move laterally across systems.
Network segmentation limits cyber incidents by separating:
Enterprise IT
Production OT
Engineering workstations
Remote maintenance
Guest networks
IIoT devices
Segmentation is one of the most effective strategies for improving Manufacturing Cybersecurity.
5. Implement Zero Trust Architecture
Zero Trust assumes no user or device should automatically be trusted.
Every access request is continuously verified based on:
User identity
Device health
Network location
Risk level
Access policies
Zero Trust significantly reduces unauthorized access across industrial environments.
6. Continuous Monitoring and Threat Detection
Manufacturers should continuously monitor:
PLC activity
Network traffic
SCADA communications
User behavior
Engineering workstation activity
IIoT device status
AI-powered monitoring tools can detect anomalies before they become major incidents.
The Future of Manufacturing Cybersecurity
As Industry 4.0 evolves toward more intelligent and autonomous operations, Manufacturing Cybersecurity will become increasingly data-driven.
Organizations that embed cyber resilience into digital transformation initiatives will be better prepared for future cyber threats while maintaining operational excellence.
Final Thoughts
As manufacturing becomes more connected, building cyber resilience is essential for protecting PLCs, SCADA systems, DCS platforms, IIoT devices, and other critical OT assets. A proactive approach that combines industrial cybersecurity, continuous monitoring, network segmentation, and industry best practices helps manufacturers reduce cyber risks, minimize downtime, and ensure business continuity.
Technosoft Engineering supports manufacturers in building secure, connected, and future-ready operations through digital manufacturing, industrial automation, IIoT, and Industry 4.0 solutions, helping organizations strengthen resilience while accelerating their digital transformation.
Frequently Asked Questions (FAQs)
1. What is industrial cyber resilience?
Industrial cyber resilience is the ability of manufacturing organizations to prevent, detect, respond to, and recover from cyberattacks while maintaining safe and continuous operations.
2. Why is PLC security important?
PLCs directly control industrial machinery. A compromised PLC can disrupt production, damage equipment, or create safety risks, making PLC security essential for operational continuity.
3. How is SCADA cybersecurity different from IT security?
SCADA cybersecurity focuses on protecting operational technology systems that monitor and control industrial processes, where availability and safety are often more critical than confidentiality.
4. What are the biggest IIoT security challenges?
Common challenges include insecure devices, weak authentication, outdated firmware, poor visibility into connected assets, and unsecured communication protocols.
5. What is the difference between cybersecurity and cyber resilience?
Cybersecurity focuses on preventing attacks, while cyber resilience ensures an organization can continue operating and recover quickly even if an attack succeeds.
Manufacturing has entered a new era where success is no longer measured solely by speed, automation, or production volume. Today, manufacturers must also address workforce challenges, sustainability goals, supply chain disruptions, and increasing customer demand for personalized products. These evolving priorities have given rise to Industry 5.0—the next stage in industrial transformation.
While Industry 4.0 introduced smart factories powered by IoT, cloud computing, robotics, and artificial intelligence, Industry 5.0 Manufacturing builds on those digital foundations by bringing people back to the center of production. Instead of replacing human workers, Industry 5.0 focuses on collaboration between skilled professionals and intelligent technologies to create more efficient, resilient, and sustainable manufacturing environments.
This shift is already influencing industries such as automotive, aerospace, industrial equipment, electronics, pharmaceuticals, and energy, where organizations are combining AI-driven automation with human creativity to improve quality, accelerate innovation, and optimize operations.
What is Industry 5.0?
Industry 5.0 is the next evolution of industrial manufacturing that combines advanced digital technologies with human expertise to create smarter, more sustainable, and resilient production systems.
Unlike previous industrial revolutions that primarily focused on mechanization, electrification, or automation, Industry 5.0 recognizes that people remain an essential part of manufacturing. Artificial intelligence, collaborative robots, digital twins, and connected systems are designed to assist employees—not replace them.
The objective is to combine the precision of machines with the creativity, critical thinking, and problem-solving capabilities of people.
The three defining principles of Industry 5.0 include:
Human-Centric Manufacturing – Technology enhances employee productivity and safety.
Sustainability – Manufacturing processes minimize waste, energy consumption, and environmental impact.
Resilience – Factories become more adaptable to market changes, supply chain disruptions, and customer demands.
This approach enables organizations to create flexible manufacturing environments capable of delivering customized products while maintaining operational efficiency.
The Evolution from Industry 4.0 to Industry 5.0
Industry 4.0 revolutionized manufacturing through automation, data exchange, Industrial Internet of Things (IIoT), cloud computing, and smart factories. However, as industries matured, manufacturers realized that technology alone could not solve every business challenge.
Today’s manufacturers face issues such as labor shortages, changing customer expectations, sustainability regulations, cybersecurity risks, and global supply chain uncertainty. These challenges require a more balanced approach that combines digital intelligence with human expertise.
Rather than replacing Industry 4.0, Industry 5.0 builds on its digital foundation by fostering collaboration between people and intelligent technologies. The focus shifts from simply automating processes to using technology to enhance human capabilities, drive innovation, and create long-term business value.
This shift marks a significant milestone in the future of automation in manufacturing.
Core Industry 5.0 Technologies
The success of Industry 5.0 depends on several interconnected technologies working together across the manufacturing ecosystem.
Artificial Intelligence (AI)
Artificial Intelligence has become the foundation of modern manufacturing. AI analyzes massive volumes of production data, identifies hidden patterns, predicts failures, and recommends actions that improve efficiency.
Manufacturers use AI for:
Predictive maintenance
Demand forecasting
Production planning
Quality inspection
Process optimization
Instead of making decisions solely based on historical reports, organizations can now respond to production issues in real time.
Industrial Internet of Things (IIoT)
Industrial IoT connects machines, sensors, production equipment, and enterprise systems into one intelligent network.
Connected devices continuously monitor:
Machine performance
Equipment health
Energy consumption
Production output
Environmental conditions
This real-time visibility enables manufacturers to improve operational efficiency while reducing downtime.
Collaborative Robots (Cobots)
Unlike traditional industrial robots that operate in isolated environments, collaborative robots safely work alongside human operators.
Cobots assist with repetitive tasks such as:
Assembly
Packaging
Material handling
Machine tending
Inspection
This partnership allows employees to focus on higher-value activities such as process improvement, innovation, and decision-making.
Digital Twins
A digital twin is a virtual representation of a physical asset, production line, or manufacturing facility.
Manufacturers use digital twins to simulate production scenarios, monitor equipment performance, predict maintenance requirements, and optimize factory layouts before implementing changes in the real world.
Digital twins significantly reduce engineering risks while accelerating product development and operational improvements.
Machine Vision and AI-Powered Inspection
Computer vision systems use AI algorithms to inspect products at speeds and accuracy levels beyond human capability.
Applications include:
Surface defect detection
Dimension verification
Assembly validation
Barcode reading
Packaging inspection
AI-powered vision systems help manufacturers improve product quality while reducing manual inspection costs.
Edge Computing
Processing industrial data closer to manufacturing equipment reduces latency and enables faster decision-making.
Edge computing allows factories to:
Respond instantly to machine events
Reduce bandwidth usage
Improve cybersecurity
Maintain production even when internet connectivity is limited
Benefits of Industry 5.0 Manufacturing
Organizations adopting Industry 5.0 Manufacturing experience benefits that extend beyond productivity improvements.
Improved Productivity
Better Product Quality
Mass Personalization
Enhanced Worker Safety
Increased Sustainability
Enhanced Decision-Making
Increased Business Resilience
Faster Innovation
Real-World Applications of Industry 5.0
Industry 5.0 is already transforming manufacturing across multiple sectors.
Automotive Manufacturing – Automotive manufacturers use AI-powered inspection systems, collaborative robots, and digital twins to improve production quality while enabling vehicle customization.
Aerospace – Digital engineering and predictive maintenance improve aircraft manufacturing while reducing development time and ensuring regulatory compliance.
Electronics Manufacturing – Machine vision systems inspect miniature electronic components with exceptional precision, improving product quality and reducing manufacturing defects.
Pharmaceutical – Smart manufacturing technologies improve batch traceability, regulatory compliance, and production consistency.
Industrial Equipment – Manufacturers leverage AI-driven predictive maintenance, connected sensors, and digital twins to maximize equipment availability and reduce maintenance costs.
Challenges of Industry 5.0 Implementation
Although Industry 5.0 offers significant benefits, organizations must address several implementation challenges.
Legacy Infrastructure – Many factories still rely on equipment that was never designed for digital connectivity. Modernizing legacy systems requires careful planning and integration.
Workforce Skills Gap – Employees need training in AI, data analytics, robotics, cybersecurity, and digital manufacturing technologies. Upskilling the workforce is essential for successful digital transformation.
Cybersecurity – Connected manufacturing environments increase exposure to cyber threats.
Organizations should implement:
Zero Trust security
Network segmentation
Continuous monitoring
Identity management
Data Quality– Artificial Intelligence depends on accurate and reliable data. Poor-quality data limits the effectiveness of predictive analytics and automation.
Initial Investment– Industry 5.0 initiatives often require investments in sensors, software, AI platforms, robotics, cloud infrastructure, and employee training.
Best Practices for Industry 5.0 Adoption
Organizations beginning their Industry 5.0 journey should follow these best practices:
Conduct a digital maturity assessment.
Define measurable business objectives.
Prioritize pilot projects with clear ROI.
Integrate legacy systems using scalable digital platforms.
Invest in employee training and change management.
Strengthen cybersecurity from the beginning.
Use predictive analytics to continuously optimize operations.
Measure performance using KPIs such as Overall Equipment Effectiveness (OEE), downtime reduction, energy efficiency, and quality improvements.
A phased implementation strategy helps reduce risk while maximizing long-term business value.
Conclusion
Industry 5.0 represents the next phase of industrial transformation, where advanced technologies and human expertise work together to create smarter, more efficient, and sustainable manufacturing. Instead of replacing people, technologies like AI, IIoT, digital twins, collaborative robots, and machine vision enhance human capabilities, improve decision-making, and optimize production processes.
As the future of manufacturing evolves, Industry 5.0 helps organizations boost productivity, improve quality, strengthen resilience, and achieve sustainability goals. More than a technological upgrade, it is a strategic investment that enables manufacturers to stay competitive through innovation, operational excellence, and a skilled, future-ready workforce.
Frequently Asked Questions (FAQs)
What is Industry 5.0?
Industry 5.0 is a manufacturing approach that combines advanced technologies such as AI, IIoT, digital twins, and collaborative robots with human creativity to build sustainable, resilient, and intelligent production systems.
Is Industry 5.0 replacing Industry 4.0?
No. Industry 5.0 extends Industry 4.0 by emphasizing human-machine collaboration, sustainability, and resilience while leveraging existing digital technologies.
What are the main benefits of Industry 5.0?
Industry 5.0 helps manufacturers improve productivity, product quality, operational efficiency, worker safety, sustainability, supply chain resilience, and mass customization while enabling faster, data-driven decision-making.
What are the main Industry 5.0 Technologies?
Key technologies include Artificial Intelligence, Industrial IoT, Digital Twins, Collaborative Robots, Machine Vision, Edge Computing, Cloud Computing, Predictive Analytics, and Digital Engineering.
How is Industry 5.0 different from Industry 4.0?
Industry 4.0 focuses on automation, connectivity, and smart factories, while Industry 5.0 builds on these technologies by emphasizing collaboration between humans and intelligent machines. It also prioritizes sustainability, resilience, and employee well-being alongside productivity.
Internet of Things in industrial automation is a game changer that will reap new benefits. It not only creates scope for innovation, but also helps solve problems at the micro level, enhance operations, and increase productivity. The main aim of industrial automation is to reduce the necessity of people in the manufacturing process and eliminate errors.
IoT in industrial automation can be achieved by mapping industrial processes, understanding micro and macro process, and their relations with machines to automate the process. This entire process involves the interconnection of sensors, instruments, and other devices over a common network to accomplish a task.
Let’s quickly drive through detailed explanations, advantages, and the role of IoT in industrial automation engineering.
What Does IoT Do For Industrial Automation?
IIoT refers to sensors, instruments, and other devices networked with industrial computer applications, such as manufacturing and energy management. This connectivity enables data collection, exchange, and analysis, which may improve productivity and efficiency and have other economic benefits. The IIoT is a Distributed Control System (DCS) evolution that uses cloud computing to refine and optimize process controls.
This is enabled by integrating multiple technologies like cybersecurity, cloud computing, machine-to-machine, 3D printing, advanced robotics, big data, cognitive computing, etc.
Practical Advantages of IoT in Industrial Automation
Scalability
Scalability in production is attained by increasing output, two goals that the digital industrial transformation facilitates and accelerates. Humans are sometimes the weakest link in production processes, which is unfortunate for the workforce. However, by removing humans from a process and delegating production to robots, businesses are able to increase their throughput.
System uptime enhancement
Like production, uptime is limited by humans. People need rest, food, a safe workplace, and ethics. Machines don’t need breaks or food. Because of automation, many factory floors are safe.
Operational efficiency
Operational automation means interconnecting and integrating systems to share information and improve operations exponentially. Computer logic lets systems respond to other needs. This basic application is everywhere now, from turning off lights to alerting global suppliers that a factory will soon run out of raw materials and need resupply.
High-security access and control
IoT introduces many attack vectors to automation systems, but it also offers a solution. Automation can be used to defend against cyberattacks. It helps defenders make their entire network visible, adhere to a policy-based approach to system configuration, management, and security, and automate many low-level maintenance tasks while alerting IT teams of more serious breaches or attack patterns.
Role of IoT in Industrial Automation
Internet of Things (IoT)
IoT concepts and technology are being explored and implemented in industrial automation. IoT helps create effective, affordable, and responsive system architectures. The goal is to create frictionless communications and interaction from manufacturing field input/output, including analyzers, actuators, and robotics, to increase flexibility and manufacturing. Industrial automation has used IoT in major applications, such as PLCs replacing banks of relays.
Internet of Things Products and Devices
Internet-connected IoT devices and systems can collect and exchange data. These products have many forms and use. Some of the examples include:
Smart thermostats, security cameras, and light bulbs can be controlled remotely via smartphone apps.
Smartwatches and fitness trackers track a user’s activity and health metrics.
Connected cars can communicate with each other and with traffic infrastructure using sensors and other technologies.
Industrial IoT systems can monitor and control factory and warehouse equipment.
IoT products make our lives more convenient and efficient by allowing us to easily collect and access physical data.
Internet of Things Gateway Devices
IoT gateways connect a network of connected devices to the internet. These devices are used in industrial IoT systems with hundreds or thousands of devices to connect and manage work.
IoT gateways are equipped with hardware and software to perform various tasks. IoT gateway devices have user-friendly interfaces that make configuration and management easy. This can include web-based interfaces, mobile apps, and other tools that make it easy for users to set up and maintain their IoT systems
Industrial IoT Development Kits
Industrial IoT (IIoT) development kits include hardware and software to help developers create applications and solutions. These kits include sensors, actuators, and other physical components for building and testing IIoT systems, as well as software libraries and other tools for developing and deploying IIoT applications.
IIoT development kits can be customized to meet the needs of a specific industry or application. A manufacturing company’s IIoT development kit may include sensors and other components used in manufacturing, while a transportation company’s kit may include GPS and other location-tracking technologies.
A Quick Recap on Industrial Automation Engineering
The Internet of Things, or IoT, is a network of interconnected, data-collecting and -exchanging devices. By allowing machines to communicate with one another and with central systems, IoT-enabled devices can be used to increase efficiency and productivity in the context of industrial automation.
In industry, for instance, an IoT system could be used to monitor the performance of individual machines and determine when maintenance is required, as well as to automatically adjust production processes based on real-time data. This can help to decrease downtime and increase operational efficiency overall.
Final Thoughts
Want to leverage the best technology for IoT industrial automation? Technosoft Engineering IoT Services will take your Industrial Automation processes to the next level of connectivity and intelligence.
Get in touch with us today for our industrial automation engineering.
Employing manufacturing process automation involves having machines complete specific tasks. This helps you stay competitive in your sector while increasing productivity, efficiency, and cost savings. There is minimal or no human involvement in the automated manufacturing process.
Automation in manufacturing is employed in areas-
Machine work like processing, inspection, and assembling
Compliance
Customer service
Distribution
Finances
Logistics
Procurement
Research
Sales and ordering
Manufacturing Process Automation companies are augmented by the Internet of Things (IoT). It has now become a global technology that has transformed entire industrial processes. IoT, in conjunction with computer automation controls, helps to simplify industrial processes and increase data automation. Automation aims to eliminate mistakes and inefficiencies, largely from people.
Benefits of Automation in Manufacturing
Quality Control of Product
Manufacturing Process Automation decreases the proportion of defect rate and is more compliant and uniform. This allows the top-quality products to reach consumers. It also reduces or eliminates the chances of human error.
By involving IoT systems in the production line, the environmental conditions, equipment performance, location of inefficiencies, and consistent process, are all kept in check. These continuous data insights enable manufacturers to pinpoint the source of quality control concerns and confidently take action.
Structured Inventory Management
Automation is rapidly transforming every aspect of inventory management. When manufacturing procedures are integrated with IoT, it enhances the supply chain and performance management.
IoT uses different technologies like GPS and Radio Frequency ID (RFID) that aid in data collection. This supplements product tracking, improves logistics, identifies potential risk, and thus, makes inventory management efficient.
Effective Maintenance Schedule
Automated equipment maintenance enhances asset utilization, extends machine life, and optimizes field crew efficiency. Manufacturing companies use automation, data science, and IoT to determine equipment conditions and accurately predict when a failure might occur.
This technology employs an in-memory database and real-time analysis to highlight areas of the machine that need repairing. This in turn reduces maintenance costs, enhances safety and compliance, and also refines the production line.
Workplace safety
IoT- based automation in the workplace has enhanced the safety of people. It addresses the large number of threats that can be prevented. This enables continuous monitoring of environmental conditions, the physical health of employees, can help limit employees’ risks, and exposure to prevent accidents from happening. It also speeds up the progress of rescue operations and prevents fire accidents.
Asset tracking
Automated asset management ensures reliability, extended equipment life, proper asset usage, and best returns on assets. Automated asset tracking involves IoT devices that enable remote monitoring and management of assets’ positions and movements.
It allows optimization of asset usage and performance with real-time data collection and helps generate valuable business intelligence. It supports the entire workflow by producing reports that notify when an asset needs to be served.
Cost reduction
Automation in manufacturing decreases the overall maintenance cost by using predictive maintenance fundamentals, ensuring worker safety during training and maintenance. It bridges the gap between floor staff and executives; detecting and resolving production bottlenecks.
It also provides insight into future changes and possibilities before the money is put into action. IoT lowers costs by prioritizing and minimizing the impacts of productivity bottlenecks through process optimization.
Bottom Line
The benefits of manufacturing process automation are limitless. As technology is becoming more accessible, automation is becoming more crucial. It leads to an increase in versatility, improves quality, helps gain competitive advantage, and focuses on work expertise. It can even enhance precision, consistency, and uptime. Now is the chance to leverage automated technologies to acquire a plethora of benefits, predictable schedules, and comprehensive budgets.
Finishing certain complex processes in factories is becoming simple and can be done without human interference. These processes such as assembling are monotonous to have humans work on it. Hence industrial automation services were involved in several assembling manufacturing processes. Every now and then we see certain trends emerging in this segment. Day after day, it is getting dynamic and more optimized to improve efficiency. There are some recent upgradations in the industrial automation space which could soon become a trending practice in all the manufacturing facilities. Here are some of the trends that are happening in this space.
Digital Twin Technologies
If you understand cloning, then grasping digital twin will not at all be difficult for you. For example, you have one machine which does a particular process and replicating the same process with one machine will not be possible. In that case, you can create virtual equipment like the original one and assign the same to perform operations in tandem. This way, your production increases and so does your efficiency. Several reports were surfacing saying how digital twin is disrupting Product Lifecycle Management (PLM). Moreover, this has been widely used in healthcare and automotive industry as well quite widely.
Converging IT and OT
Integration is the new word in the tech world. For years, IT and OT has been two different domains. But there is a need to bridge both together. Under OT, one does monitoring and controlling equipment. On the other hand, under IT a lot of support management activities take place. But efficiency and productivity is said to increase only when both the operations are interconnected. A lot of research has been going on to converge both of these. By the end of 2019, we can possibly get to see manufacturing facilities with the convergence of both these operations.
Cobot Usage
Cobot or Collaborative Robots as they’re called is now emerging. In 2018, its worth stood at US$710 million and same is said to surge to a whopping market worth of US$12.3 billion. These collaborative robots are said to increase production lines, increase productivity and improve employee safety. It is considered to be more affordable that even SMEs can afford having one and keep improving their efficiency from time to time. Europe, APAC and North American regions are heavily investing in this technology and soon we can see a lot of upsurge in investments and usage.
Augmented Reality
Augmented reality is not an alien term, but the advancements it offers for your manufacturing facility is something new. In the manufacturing space, augmented Reality is considered to have impacted product lifecycle management. Right from monitoring process improvements to inventory management and new product introduction, AR does everything to make your manufacturing process simple and efficient. Experts even say AR could allow one to look into the product pointing to the problem area. This is said to actually improve your efficiency and let you go ahead. Also, AR is widely used in different industries for different processes.
Technosoft Engineering with an experience of two decades in the field of Industrial Automation Services offers impeccable solutions to simplify complex processes. Refer to this page to understand how the offerings of Technosoft are unique and how it keeps your ante up in the market. Most importantly, checkout Essential Processes to Make a Robust Robot Design.
