Question:
Answer:
Question 1
My working definition of an autonomous robot is: a robot is autonomous if, absent real-time interference from a human agent, it has the computational resources - both hardware and software - to estimate how it is physically embedded in the environment and compute the best possible actions bounded by some constraints to perceive and move if necessary to achieve a set of goals. The capacity of a robot to assess its present state (how it is physically embedded in the environment) is a fundamental component of autonomy, according to this working definition. Then it must have the processing resources to do any action within boundaries, to improve its perception of the surroundings if necessary, and to move if necessary to attain a particular objective.
Additive manufacturing (AM) is a technology that uses layers to manufacture three-dimensional (3D) physical items from digital models in a single step, allowing creatives, engineers, architects, and designers to build unique designs in a single step. The introduction of sophisticated technology, together with demands for more ecological and resource-efficient practices, as well as trends for future buildings and designs, are all contributing to the rise of futuristic buildings and designs. Approaches such as process automation offer a big retreat from conventional methods of construction. This has largely been investigated in terms of robotics.
Additive Manufacturing by Robot
Additive manufacturing (AM) is a broad word that refers to a range of processes for creating three-dimensional structures, many of which are custom-made. Different AM techniques, such as 3D printing and rapid prototyping (RP), have progressed from making simpler models that aid in the visualisation of an end product to generating structures that function as final products. AM technology is still gaining traction, and it's especially useful for small businesses and developers that want to make low-cost prototypes and bespoke components quickly.
AM technology has mostly been used to create tiny components and goods. This is because most classic AM methods need the structure to be created "in-box," that is, within some form of container within the AM device. As a result, the AM machine must be larger than the structure it is creating, which has its own set of constraints. However, as more and more projects explore at AM on a wider scale, this is increasingly changing. AM has already been used in a number of housing projects, and the Dutch MX3D-project has built a metal bridge entirely utilising AM and a robot manipulator.
For example, AGVs are used to transport products in factories and warehouses, while flying robots (also known as drones) are used for disaster response, and underwater robots are employed to look for and uncover shipwrecks at the lowest depths of our oceans. While the usage of robots has shown to be extremely beneficial throughout time, these instances in no way represent the usage of true artificial intelligence.
Question 2:
The Internet of Things (IoT) made its way into the workplace in 2017, and it is now at the centre of industrial digital transformation. The Industrial Internet of Things (IIoT) is a subset of the Internet of Things (IoT) solutions for smart manufacturing (IIoT).
Key benefits of IIoT in an industry context
- Improved and intelligent connectivity between devices or machines
- Increased efficiency
- Cost savings and
- Time savings
- Enhanced industrial safety
The IIoT is used in a wide range of sectors. The automobile sector, for example, employs IIoT devices in the production process. Industrial robots are widely used in the automobile sector, and IIoT may assist prevent production disruptions by proactively maintaining these systems and detecting possible faults.
The replacement of people in multiple processes by linked devices has fundamentally changed the industrial industry's face.
- Advanced analysis. The integration of IIoT-connected devices and relevant software solutions enables powerful analytics to predict failures and optimize maintenance. Sensors monitor networks and integral devices, measure performance indexes, assess operation features, alert users about malfunctions and react to abnormal events. Advanced analysis dramatically increases equipment efficiency, performance and uptime, as deficiencies do not go unnoticed.
- Inventory level monitoring. In maintenance, repair and operations environments, IoT-connected devices monitor distributed inventory and tank fluid levels, the condition of wear parts and production rates, which enhances the communication between manufacturers and suppliers. Also, proper monitoring enables quick and effort-efficient identification of issues that adversely impact product quality or time-to-market.
- Remote process monitoring and equipment configuration. Employees can remotely collect information on production processes and check whether they or their outcome meet specific regulations and requirements. In addition, they can tune and configure devices remotely, significantly saving time and effort.
- Abnormality reporting. Human participation is no longer required to identify possible abnormalities in the performance and condition of equipment: IIoT-connected machines alert responsible personnel about the deterioration of equipment, leaving employees to only take remediation steps.
- Virtual equipment management. Automated devices allow employees to fix many performance issues via virtual networks, without being physically present, thus streamlining the management and monitoring of equipment. Also, virtual equipment monitoring allows employees to be aware of device location, including of movable assets.
As you can see, connected devices integrate employees, facilities, equipment and databases into comprehensive networks that can improve management at all manufacturing stages.
Question 3:
The skills that could be required to bring about an Industry 4.0 transformation is to think about IIoT in the context of an autonomous assembly line. It could include 3D printers and other Additive Manufacturing techniques running alongside Computer Numerical Controlled (CNC) lathes and newer machines capable of executing highly variable, multi-step processes using robotic vision and Artificial Intelligence. In addition to this, we may have collaborative robots that work alongside humans. This calls for not only multiple skills sets but, in many instances, the blending of those skills. These skills will cut across silos and specializations to create a whole new category of technology professionals – ones who understand the convergence of operational technologies and information technologies.
The five most important skills required will include:
Cybersecurity – Cybersecurity is already a major concern for companies that, to date, probably have not had to think much about it. When few of the older machines have been turned into data-generating network endpoints and linked together with new equipment, which in turn is tied into backend ERP systems and supply chains, a company's attack surface expands exponentially.
Data scientists – The IoT deployments fuelling Industry 4.0 will generate vast quantities of data. All that data will need to be captured and analyzed so it can be used to improve machine performance, reduce resource consumption, assist in quality control, make supply chains more efficient and introduce new products and services.
Networking – Connecting machines to each other and to the command & control systems that will oversee them will require the skills of a highly skilled network engineer. They will have to be up to date on WANs, edge networking and fog computing as well as next-gen 5G networking technologies, Wi-Fi and the low-power LAN protocols that IoT devices often run on.
Software engineers, application developers & programmers – These jobs will be required in various forms from one end of the Industry 4.0 ecosystem to the other. Manufacturers will need skilled manpower to write and modify programs for machines as well as develop new interfaces for their human counterparts to interact with them.
Architects – IT architects will have a role to help systems engineers on the operational side meld the physical and logical worlds. People in this role will be required to understand the full dimensions of a company's existing business, its processes and its digital transformation goals and then figure out how to tie it all together using technology.
It is imperative now that we utilise this opportunity to prepare skilled manpower for the future of the manufacturing industry. The world belongs to the workforce which has the skills to survive through multi-skilling and skills for integrating specialized skills.
