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Mills In The 4.0 Era

The palm oil milling process has been quite stagnant for many decades without any major transformation using the latest technological innovations. The concepts and processes used in milling are predominantly based on those formulated and developed in the 1950s. Until recently, the majority of palm oil millers have been treading on safe ground, without having the confidence and tenacity to venture into unfamiliar territory by taking calculated risks. With the marked increase in CPO prices in recent times, most companies are trying to play safe while reaping unprecedented profits due to

this surge in prices.

The palm oil industry has been hard hit with labor shortages as it heavily relies on unskilled foreign labor for many years. More so now, it has worsened with the lockdowns imposed during the global COVID-19 pandemic, the effects of which are still predominant. Seeking a career in the plantation sector has not gone down well with millennials, who are still stigmatized by the connotation that working in an “estate” is deplorable. To attract more locals from the younger generation to work in plantation sectors, there has to be a major rejuvenation and shake-up of the plantation industry as a whole. The way to the heart of this “tech-savvy” generation would be to be able to entice them via the usage of technology as a cornerstone in the plantation industry.

With the advent of Industry 4.0, more and more palm oil mills have embarked on a journey to use the latest technology as part of their day-to-day operations. Industry 4.0 takes the emphasis on digital technology from recent decades to a whole new level with the help of interconnectivity through the Internet of Things (IoT), access to real-time data, and the introduction of cyberphysical systems.

There is an increased application of new technologies in both downstream and upstream manufacturing operations. Industry 4.0 is the new fourth industrial revolution in which automation and diagnostics play an important part, providing extensive capabilities in the field of manufacturing. I would like to highlight a few topics below which are of prime interest in recent times.


Using robotics technology in palm oil milling has enhanced automation systems and performs mundane tasks precisely and at a fraction of the cost. Robotics is progressively leading to efficiency in improving the manufacturing of quality products while maintaining the value of existing process controls.

This technology is helpful to perform repetitive complex hazardous tasks such as in high-temperature working environments while working continuously with precision and for longer durations in operation lines. Many robots operating in intelligent factories use artificial intelligence to perform high- level tasks with the ability to increase their knowledge base and learn from experience gained in various diverse scenarios.

Collaborative robots known as cobots are capable of working in collaboration with palm oil mill operators. Dirty, unsafe, repetitive, or even time-sensitive tasks can be efficiently performed by these cobots. Some examples of where cobots could be used would be in the autonomous steam & temperature control at the Digester using automated robotic arm actuators through control sensing signals and automatic control of crude oil-water dilution for efficient oil separation to reduce oil losses at the Clarification process.


As an add-on module to our Mill Micro Macro Program (MMMP) which ABS has successfully implemented in numerous palm oil mills across the region, we have also installed a Realtime Alert Supervision (IoT Remote Monitoring) System for critical operating stations, where the IoT sensors will constantly read the operating parameters and will compare it against the control limits. Once the parameter detected by the IoT sensors is above or below the control limits, an Alert Notification is triggered and pushed to the mobile device to alert the mill Supervision personnel. They will then have to physically proceed to the alerted machine and perform a recovery by entering the root cause and action taken to close the alert.

The key feature of this Alert Supervision System is to ensure that the Mill Management team is equipped with the transparency to view critical mill operating parameters and is provided with visibility to verify that out-of-spec parameters have been rectified promptly by designated mill Supervisors.

The Alert Supervision System also allows the Mill Management team to track the elapsed response time of the Supervisor for a particular out-of-spec parameter. Numerous clients using our Alert Supervision System have given positive feedback that this has resulted in taking transparency and awareness of mill operations to the next level.


Taking a step further which is unprecedented in palm oil mills, automated drones could be flown throughout the mill using customizable flying routes using a “sense and avoid” function via a pre-scheduled time and duration. The automated drones could provide visual data, thermal data, photos, videos, and 3D images of critical parameters resulting in actionable reports due to accurate data capturing and report generation via the preset drone monitoring.

Mill operations and maintenance issues could be monitored and improved drastically due to visibility provided by the drones, even as far as the effluent ponds and water catchment areas which are usually neglected due to their distance from the mill. Worker awareness and productivity could be improved as their operating stations are closely monitored by drones.

Drone monitoring could assist remotely in detecting other threats to the mill premises such as potential fire hazards and water leaks thereby reducing accidents at mills. Live video feeds from drones could be sent to the mill head’s mobile device, a central monitoring facility, or even directly to emergency responders.


Traditionally, palm oil mills have been using the Preventive Maintenance methodology for decades as an integral part of milling operations. Preventive Maintenance is the regular and routine maintenance of equipment and assets to keep them

running and prevent any costly unplanned downtime from unexpected equipment failure.

A successful maintenance strategy requires planning and scheduling maintenance of equipment before a problem occurs. A good preventive maintenance plan also involves keeping records of past inspections and the servicing of equipment. However, AI Predictive Maintenance is a technique that uses condition-monitoring tools and techniques which may include historical and real-time data analysis to monitor the performance of equipment during its operation to anticipate problems before they occur. Its techniques could be used to detect anomalies such as drastic changes in pressure, temperature, vibration, sound, and current in the operation and possible defects in equipment and processes so that designated personnel would be able to carry out the required rectification works before resulting in component failure.

With the advancement in recent technology, we are now capable of using AI’s Predictive Maintenance power to optimize mill maintenance effectively. The AI ecosystem collects and processes data locally instead of collecting information and sending it to the cloud. AI continues to evolve through a process of self-learning and self-correction which enables faster adjustments to local conditions. This provides users with real-time data direct from the equipment itself and enables faster and more reliable feedback via changes in vibration, sound, etc. High costs associated with additional hardware and cloud-based data storage could therefore be avoided.

Ideally, Predictive Maintenance allows the maintenance frequency to be as low as possible to prevent unplanned Reactive

Maintenance, without incurring costs associated with doing too much Preventive Maintenance.

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