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From Automation to Autonomy: How to use Swarm Autonomy to swiftly migrate?

Updated: Oct 11

A fundamental shift from industrial automation to autonomy is noticeable all over the globe with a focus on better integrated OT, CT, and IT systems.

Here you will get to know the difference between Automation and Autonomy, why we do not see Autonomy everywhere yet, how to know when to move toward Autonomy and how to value such system.

Understand the “Why can’t we?”


[Three recurring questions]

Plant managers keep asking these three questions to their automation engineers:

  1. How to adapt faster to the variety and volume changes of the production?

  2. How to act faster in case of an unpredicted line-stop or logistical bottleneck?

  3. How to make sure we take full advantage of the expensive equipment we buy?

The most frequent answer is, “we will think about it” and the final solution is often to add a decision fork in the system, an alert, or any other reactive process. But the right question is not “How to?” but “Why can’t we?” To answer, “why can’t we?” every factory should be aware of the macro-trend and challenges they will face.

[Challenges] The arrival of high-mix low-volume, short lifecycle, short lead-time, and localization bring about a new set of challenges:

  • Tools and processes change more regularly and need regular updates

  • Logistical low-value tasks need to cost less and less

  • New factories need to be set-up fast and with the least labor headcount

  • New type of equipment fast onboarding and efficient use to reach best OEE

Today, traditional automation cannot keep up with the uncertainty and continuous decision making needed to deal with these challenges. Systems will need to evolve.

 

Analogy with human mobility.


Modern commuters wish to move faster, change jobs regularly, they may commute longer hence try to reduce idle time as much as possible.

This triggered a push for a more diverse mobility offering including bus, MRT, trams, free floating fleet and more.






If, like a work in process (WIP) material, one faces the need to go as fast as possible from A to B, one will need the following:

  • Perfect route timing with available mobility tools

  • Synchronization of your mobility tools availability with your routine need

  • Little to no idle time when changing from one mode to another

  • A clear cost/time ratio to plan based on your priority


For example, the train, specialized in large passenger batches, needs to synchronize arrival time with buses departure time, knowing that buses are capable of smaller batches.


In a mass mobility system, why can’t we synchronize the bus and the train so that nobody waits?

The right implementation of the right technology is still too difficult:

  • Complexity of operation and decision-making

  • Lack of communication between the different automated networks

  • Lack of real-time data and context

Fortunately, new systems and technology are being developed and applied in mass mobility and intralogistics.

 

How do I know if my factory needs automation or autonomy


A factory will know when it feels the below 4 pain points:

  1. Manual or automation work reached a productivity plateau

  2. Consistent inventory gap, and identified need to digitalize the production

  3. Supervision work is overcomplex and relies on less than 2 qualified people

  4. Recurring reconfiguration efforts due to production changes

Here is a brief comparison between Automation and Autonomy in the case of a material replenishment use case, different input/output level:

Automation

Autonomy

Material status

  • ​Ready/Not Ready

  • Time before readiness

Material order trigger

  • Delivery spot

  • Expected delivery time

  • Select batch size

  • Delivery zone

Material onloading (secondary tasks)

  • Humans oftentimes

  • Robotic arm control

  • Robotic arm/Conveyor control

  • Process status

  • Error handling

  • WMS update

Material transport

  • Queue task to move from A to B

  • Material type awareness

  • Robot matchmaking

  • Contextual priority

Estimated arrival time

  • Fixed cadence = fixed throughput schedule

  • Re-calculated regularly

  • AI-estimation

Material storage status

  • N/A

  • Storage occupancy awareness

  • Choose alternative storage

Bottleneck handling

  • Deadlock/traffic error

  • Automated workaround

  • Resolution options

Material offloading

  • Human or robotic arm

  • Robotic arm/Conveyor control

  • Process status

  • Error handling

  • Machinery handshake

Delivery status

  • Robot task done

  • WMS update

  • If error, reschedule other tasks

In conclusion, the missing piece is technology to arbitrate change in real-time and drive optimization. FARobot is one of the rare companies to pioneer such technology with its Swarm Autonomy platform.



Autonomy in practice

FARobot’s Swarm Autonomy allows factories to migrate systems from automation to autonomy and address the above pain points. Swarm Autonomy debuted at Automation Taipei 2022 offering a deep dive into what autonomous factory may look like.

The demonstrated system consists of two automation systems:

  • A robotic arm for rack sorting

  • An AMR fleet made of three distinct brands

Autonomy was realized through three key features:


1. Dynamic scheduling of all resources The demonstrated system was using a fixed route, but the Swarm Core was free to choose any robot depending on their availability, current location, capability, and battery level. In a factory, obstacles and safety stop trigger can contribute to readjusting task assignment to best suited robots.

In the case of automation, such a change may be decided by a human supervisor after receiving a system error alert.

In an autonomy system the sequencing and scheduling module is the hidden orchestrator. In the below video each task was queued and rescheduled depending on the main variables, battery level and robot availability.


2. Parallel task execution through Smart Matchmaking During the demo, a workflow triggered a rack transport to the robotic arm. It meant that an empty rack had to be ready to receive the cargo. Fortunately, the advanced workflow synchronization anticipated such a need and triggered two parallel tasks. The benefits included reduced material idle time and higher robotic arm and AMR’s OEE.



3. Process and data awareness To make real-time autonomous decisions, the system needs to access reliable data from every device. For that, tight integration is realized through the Swarm Protocol. This innovative communication protocol acts as a data highway to satisfy monitoring and control needs. In this case the robotic arm integration allows the system to synchronize every sub-system and transfer the payload autonomously.



 

Now that Autonomy is possible today, why don't we see it everywhere?

The short answer is, such system is rare and requires key technologies that only a few companies understand and can turn into commercial product, FARobot is one of them.

FARobot system is the one-platform solution designed to build autonomous systems.

FARobot's Swarm Core platform is already deployed in different sites to move from automation to autonomy.

Here are some snapshots of FARobot system in operations:



Why make an investment in such a system and how to value such system’s benefits?


When evaluating two systems, is it necessary to compare two systems upfront costs. But the only way to make an accurate comparison is to use the Total Cost of Ownership (TCO).

The TCO offers a view on all management cost and savings related to operating the system over the years. It includes the system maintenance, the system adaptability and correlated OEE you expect to reach. It can also include the throughput variability you may expect to be handle by robots or the cost of change (routes, layout, capability).

Automation may reach a satisfying productivity level but has hidden costs:

  • It cannot improve to guarantee best service time

  • It has a predefined OEE with little room for adjustment

  • It cannot adjust to improve productivity further

On the other hand, an autonomous system will provide hidden benefits:

  • Less human decision-making = less errors

  • Less material idle time = higher throughput

  • Freedom to change layout to production change

In fine valuing Autonomy is like valuing adaptability. If your factory is to become more agile and adaptive, then Autonomy will revert in high Return on Investment (ROI).


As illustrated below, FARobot's encourages its customer to build a virtuous loop through a thorough implementation of Swarm Autonomy.

The expected benefits are:

40% saving in integration time resulting in:

  • Integration budget saving: faster integration of old and new systems

  • Deployment budget saving: reduced training and onboarding time

  • Easy scalability: less time and effort into scaling across floors and sites

+25% in equipment occupancy

  • Equipment are used more often and cause less material idle time

  • Mobile robots are at the best place at the right time to increase their useful time

-50% in robot maintenance time

  • Better error management, update management reduced field maintenance time

  • Better battery management and correct payload transport reduces maintenance cost



To know where to start with Swarm Autonomy, contact FARobot from www.farobottech.com

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