6 Ways Lean Manufacturing is Enabled by Collaborative Robots

6 Ways Lean Manufacturing is Enabled by Collaborative Robots

The emerging technologies in flexible, collaborative robotics are a synergistic fit for lean manufacturing.

Traditionally, lean manufacturing environments have eschewed technology in favor of simple visual systems and flexible processes.  A new generation of smarter, faster and lower cost robots is changing that.

The emerging robotic systems are collaborative – they work with the associates on the floor.  This means that instead of requiring 100% process automation in the application, these new robots can be used to automate the appropriate part of the process.  That makes them more flexible and a better fit for the lean world.

The question then becomes what are the use cases where we can apply these new robots and how do they align with lean manufacturing protocols?

Process overview:

In a Lean Manufacturing environment demand pulls production.  Safety stock and batching is eliminated to drive the most efficient production process.  Kanban quantities are pulled in standard containers to the point of use, typically a flexible cell, only when needed.

In this scenario the pull signal generates a pick and transport from the stock area of an exact order kit to the point of use, typically a designated Kanban location, and the empty container is retrieved.  This may require an associate to physically pick, retrieve and transport the container from the interim supplier stocking point to the point of use.

Let’s look at the opportunity for collaborative robots to add value in this process.

1.      Lean Manufacturing is demand driven.

Demand driven strives to match production exactly to the customer specific order configuration.  The end goal is to have production in lock-step with demand to deliver exactly to demand without variance or waste.

Robotic automation has always been good for high-volume, repetitive tasks.  Maturing robot technology can now be applied to lower-volume tasks that up to this point have required human intervention.  This includes better navigation technology that allows the robots to be truly autonomous and smarter algorithms that enable more complex collaborative tasks.

Robots can now support picking and delivering unique component kits for unique customer configured orders.  The collaborative robots are smart enough now to pick and deliver order-specific configurations and this takes the next step towards enabling true demand driven response.

2.      Utilizes flexible manufacturing methods to match supply to demand. (cells)

Flexible manufacturing enables the work cells to flex to both the volumes and configurations of orders.  In best practice these lean repetitive manufacturing flows minimize change-overs. Through cross training associates the cells have the capabilities to flex to the demand-driven customer orders all the way down to a ‘lot of one’.

In this environment the new generation of smarter, collaborative robots have the ability to match the flow and flex to low volume, order specific picks.  These robots can easily be ‘software configured’ to map to changing demand configurations in support of flex and flow of the cells.

3.      Eliminate waste (travel time and touches)

Using robots to pick and transport standardized kits to point of use maps directly to waste elimination (Kaizen).  Traditionally this type of automation was too rigid (conveyors, ASRS) and ran counter the flexibility required by a lean process.  The new flexible robots can automate the process and be quickly reconfigured for a new use without the traditional cost and capital requirements.

Not only can the robots increase the efficiency of the operations in terms of throughput they also eliminate different types of waste in the process.

  • Transportation waste
  • Queue and wait time waste (robots are instantly available)
  • Pick waste
  • Reduction of the number of human touches in the process

In additional the robots are ‘lights out’.  They are not constrained by shifts or skill-set availability.

4.      Utilizes deliver to point of use with standardized containers with small lots to visible Kanban.

Robots will deliver the standardized container replenishment or the order-specific kit directly to the point of use exactly when it is needed.  Traditional automation systems couldn’t manage simple visual signals to drive replenishment (empty bin, square on floor).  Collaborative robots will flex to volume (up and down) without having to add humans.  They will wait patiently for the pull signal and execute with no waste to deliver to the point of use.

5.      Utilize central supermarkets for common components that are pulled to the floor as needed by Kanban.

Robots can also be used the same way to replenish consumables to the cells from a supermarket.  In a supermarket use case the robots will receive the pull signal from the Kanban locations in the cells and automatically deliver a fresh bin replenishment to the point of use and remove the empty bin.  No human interaction or interruption of flow.

6.      A focus on six-sigma quality.

Removing human touches from the pick and transport process removes potential qualify problems.  For example, in an electric static sensitive environment the robot can be configured to always respect the electro-grounding requirements.  A variety of real-time environmental sensors can be built into the robot picking and transport application to monitor the quality being delivered.  The robot becomes a TQC platform.

Robots are perfect for six-sigma and TQC efforts because they don’t make mistakes and they don’t create potentially damaging touches in the pull and deliver process.

Summary:

A new generation of robots has matured to the point that they will enable many Lean Manufacturing use cases.  A perfect starting point is the pick, transport and delivery of components and kits to the point of use in production.  In the continued push to eliminate waste, drive perfect quality and deliver to direct demand a new cadre of robots is ready to lend a shoulder to the wheel.

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