Replacing that Old Assembly Machine – Throw out the hardware but keep the “Learnings”

Replacing that Old Assembly Machine – Throw out the hardware but keep the “Learnings”

Every plant has one of these. That old, 20+ years, workhorse assembly machine that makes that mature industrial product that refuses to die, (both the machine and the product). It's that “meat and potatoes” product that we have newer offerings for but it has a large number of installations in the field and is both routinely speced into new designs while also providing a steady spares and replacements business. This product refuses to die!

The machine that assembles this product is old, worn and requires frequent operator intervention to keep it running while maintenance dreads working on it. Over the years, a hodgepodge of modifications and patches have been applied, both mechanical and electrical, to the point where the documentation, if it exists, bears little resemblance to the actual machine. Safety guarding was added at some point, a station has been deactivated, “as it never quite worked from day one”, and an inspection station has been added just before the auto unload. To make matters worse, we only have one operator that gets production out as she's “learned” all the idiosyncrasies over the years, to keep it running, (as she knows where to “poke” the feeding track when it jams and how to change setups, “just right”.)

BUT, it's our only machine and it works!

Stipulating that an analysis has been done that this product will be business viable for the foreseeable future and we need to eliminate these inefficiencies, the machine has already been depreciated from a financial perspective and we have the justification and it's way past time, to replace it. The question now becomes how do we do that?

There is a continuum of options ranging from designing a new system with a “blank sheet of paper” approach all the way to simply “cloning” the existing design with all the patches and improvements made over the years. The most efficient answer usually lies somewhere in between and requires some analysis to identify.

When a custom assembly system is first designed and built to some performance specification, prior to deployment it typically undergoes a Final Acceptance Test and even a Site Acceptance Test to assure that specifications have been met by the designer/builder. This is all good but running 100, 1,000 or 10,000 cycles under the controlled conditions of the test, even with using actual operators, is no substitute for the real world experience of operating the machine on a production basis, day in and day out, with various operators, over a prolonged period of time, (years in this case.) These are the Learnings that must be incorporated in the new machine!

These are both the “hard learnings” such as a better understanding of the precision required in each of the stations/operations, the “wear” characteristics of certain parts of the machine as the product feeds through it, a more efficient use of force functions and speeds as well as the identification of any logic sequence change that may enable the machine to operate at a faster rate and the “soft learnings” such as a more ergonomic interface between the machine and the operators and maintenance crew, easier quick-change of tooling, perhaps parts feeding alternatives or better unload options that simplify the next operations process, be that a packaging or a sequential assembly step, as well as other soft attributes that were not anticipated or foreseeable in the original specification.

Since the machine has been in operation and making good product for some time, the original architecture has proven it's merits but time and experience have also exposed some of the weaknesses of that initial design. Weaknesses that maybe were inherent in the way the machine was originally specified. The difficult question to answer is always, is it the architecture that led to these weaknesses? Or was it the execution based on limitations of the technology or components available at that time? In either case, making significant changes to the architecture and functional algorithm involves development risks that we may not need to take if after careful review, we find that the original design architecture is sound and it is simpler to build on the original design architecture and design intent with more enabling components or better execution.

If we are able to accomplish this, it means that we are making a 2nd generation design which builds on all the hard work of the original designer/builder while benefiting from the testing that we have as our “learnings” from the machine being in service for many years. In essence, leveraging our original investment as any new design invariably presents new problems to solve and optimize. Where possible, it's advisable to avoid those risks unless we have some compelling reason such as some performance limitations of the original design which do not meet our requirements.

Finally, fidelity to the original design architecture and design intent does not preclude using higher performance components such as sensors, motors, force actuators and controls that offer greater flexibility, ease of use or improve machine performance/safety BUT unless there is some compelling motivation such as labor content reduction, IoT connectivity requirements or some other planned integration with upstream-downstream processes, it's advisable to resist the urge to add unneeded levels of complexity in the new system which will affect not only the machine's development and optimization time but most important, will introduce new and additional personnel burdens as additional operator or maintenance training will probably be required.

To summarize, in building a next generation machine for a process that we have been running over many years and for which the present machine has outlived it's serviceable life; we perform a detailed survey/analysis of the historical experience with the existing machine, both the hardware and it's performance as well as how well it's held up under full time production conditions while simultaneously, we also review the human-machine experiences with this system over that time, both operators and maintenance. These constitute our “learnings” that we will use to faithfully reproduce all the “good” aspects of the original machine architecture and design while solving any problems or weaknesses so that we can leverage our original investment and benefit from our experience. Simultaneously we resist the urge to stray from the “proven” design architecture simply because there are other form factors available to us today. After all, the recipe has already proven that it works, why re-invent the wheel!

Your thoughts and comments are appreciated.


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