APAC Industrial Robotics: Driving Smarter Production and Efficiency

The adoption of industrial automation is increasingly associated with the productivity, quality, and flexibility of production management practices among manufacturers in the Asia-Pacific (APAC) region. Notably, the utilization of robotics extends beyond large automotive manufacturing facilities characterized by highly repetitive processes; it is also being implemented in various other industries.

The adoption of the technology is growing in a variety of electronics, food processing, pharmaceutical, logistics, metalworking and other manufacturing sectors where accuracy and repeatability are critical. Other demands by manufacturers are for automation that can adjust to smaller batch sizes, evolving product designs and stricter operating specifications.

Stay ahead of the industry with exclusive feature stories on the top companies, expert insights and the latest news delivered straight to your inbox. Subscribe today.

The use of robotics is evolving from stand-alone devices to integrated components of the production process, as robotic hardware becomes more easily integrated with sensors, vision systems and industrial software. The manufacturing sector is particularly important in APAC, as there is a diverse base of manufacturing, including established industrial economies and rapidly developing industrial production markets, all of which have different types of robotic capability needed.

Shifting Demand and Adoption across APAC

The need for flexibility, not only for the sake of automation, is influencing the evolution of industrial robotics in APAC. Robotic systems are still being used by high-volume manufacturers for welding, assembly, palletizing, material handling, and machine tending applications, with additional applications becoming available in inspection, packaging, and precision handling. The manufacture of electronics is a good example since it is often made up of small parts, close tolerances and frequent product changes.

The trend of connected manufacturing is also influencing the selection of robotic equipment. Payload, reach and cycle speed are no longer the only metrics used to evaluate a robotic arm. Manufacturers are thinking about the ease of exchange of information between equipment and production systems, sensors and quality-control platforms. Information collected from the robot operation can be very helpful to understand cycle time, equipment utilization and any repeating process variation.

Collaborative robotics is becoming more important as automation needs to work alongside human workers. Collaborative systems are not meant to replace complete production processes, but rather to be used in support of various production tasks, including component handling, inspection, packing and machine loading. These applications are especially helpful in situations that require human decision-making and repetitive physical tasks.

Integration Challenges and Practical Solutions

One of the key practical issues yet to be resolved is how to integrate robotics into existing factories. Numerous APAC manufacturing plants have equipment from various stages in their plant development process. Communication protocols might not be easily compatible with modern robotic controllers on older machines.

"Information collected from the robot operation can be very helpful to understand cycle time, equipment utilization and any repeating process variation."

There is normally no need to change existing equipment, and it is commercially impracticable. Instead, integration can be done by using communication gateways, by using modular control systems and standardized interfaces that enable the interaction between newer robotic equipment and the existing production equipment.

Another area that needs attention is the workforce capability. Although modern robotic systems can undertake complex tasks, a technology specialist needs to know how to program, calibrate, maintain and diagnose the system to make it function effectively. Technical training and cross-functional development can help manufacturers meet the skills need.

Maintenance, production engineering and quality personnel can be trained to know how to work with robots instead of having to depend on a handful of experts to provide this information. Routine adjustments could also be simpler with more intuitive programming tools for plant personnel.

A related challenge is the production variability. A robot working in one product format can become inefficient if there are changes in the product specifications. Flexible tooling and machine vision provide a viable solution.

A robot can use vision technology to detect the position and orientation of components, and adaptable end-of-arm tooling can enable a single system to execute multiple, related tasks. The manufacturers can have the robots in their production line handle more production requirements without having to rebuild their entire workcell every time the production specification changes.

Technology Advances Creating Value for Stakeholders

The incorporation of artificial intelligence and machine vision is improving the capabilities of industrial robots, allowing automated systems to understand the production context better. Robots with vision can recognize components, detect positioning errors and be used for automated inspection.

These types of features can be desirable in production settings where parts are not necessarily identical or where there is customization. Edge computing enhances responsiveness by processing production data near the machines instead of depending entirely on remote systems.

Another field that is becoming important is predictive maintenance. Robots with mounted sensors can track vibration, temperature, motor usage and other parameters of the running machines. Having such information analyzed can assist the maintenance team in identifying patterns that relate to equipment wear. Rather than conducting maintenance at regular intervals, plants can base their decisions on more specific needs, depending on the actual use conditions.

The use of simulation and digital modeling is also enhancing deployment. Robotic movements, workspace layouts and production sequences can be tested in a virtual environment before installation of physical equipment. It is possible to identify the potential collisions, reach restrictions, and sub-optimal movements at design time. The simulation can reduce commissioning efforts and familiarize production teams with the way that a new automated cell will work prior to its use in manufacturing.