Is it possible to make money by using robots in unconstrained environments?

Citation

Buckingham, R. (2001), "Is it possible to make money by using robots in unconstrained environments?", Industrial Robot, Vol. 28 No. 3. https://doi.org/10.1108/ir.2001.04928caa.002

Is it possible to make money by using robots in unconstrained environments?

Is it possible to make money by using robots in unconstrained environments?

Rob Buckingham is Managing Director of Oliver Crispin Consulting Ltd, Heneaze, Bristol, UKEmail rob@ocrobotics.co.uk

Keywords: Robots, Systems integration, Food industry

We all know that robots are good at paint spraying and inserting windscreens. We are probably less convinced about using robots in situations that are less controlled or less constrained – e.g. ploughing fields, chopping down trees or picking tomatoes. In many cases a solution has been demonstrated, but then we seem to reach an impasse. The challenge is can we engineer solutions to these complex unconstrained problems that fit within the customer's commercial and operational framework?

In a past life as an academic I was involved in automated manipulation of textiles, wires, fish, chicken, meat, bread and even people (surgery). Whilst we built machines and gave reasonably convincing demonstrations the customers did not come rushing back. One of the objectives in setting up OCC was to supply innovative robotic equipment to customers. It has been an interesting learning curve. Our best customer to date is HP, but the task is totally constrained. We still hanker for an opportunity to build robotic systems for unconstrained environments, but the opportunities are few and far between.

In this personal viewpoint I have tried to identify some of the key issues when trying to make money out of complex robot systems. The Editor indicated that controversial is OK so an empty post bag would be a shame.

1. 1.

   Humans are extraordinarily good at adapting to complex, changing environments. In particular our sensors and associated decision making software are robust and have a huge working range. Worldwide there is no shortage of people, although appropriate training and location may be an issue. Robots are entering a very competitive market.

2. 2.

   Developing a new and complex piece of equipment without a clear understanding of the commercial objectives is fraught with danger. There needs to be an openness on the part of the potential customer to reveal commercial and operational information in addition to the technical specification to the machine developer. Strong partnerships are essential.

3. 3.

   Would it be fair to say that you only find out what the customer really wants some time after the first demonstration? Sometimes you never find out what the customer wants: goal posts are seldom stationary, and key managers are moved on.

4. 4.

   Building a demonstrator is only10 per cent of the cost and effort required to implement the solution in the production environment. For robotic systems producing the demonstrator can take two years and cost someone a substantial amount of money. There are few customers around who are willing to pay for this early stage development. Some customers may be willing to come in after the first demonstrations to bring the product to market. Most will only buy when a machine is clearly shown to be doing the business. So, there is an issue of who pays for the R&D. Within Europe, the EU has and continues to part-fund developments, although there are few examples of devices making it to the production floor and the period from idea to reality is at least ten years. One view of government funding is that it clouds the commercial objectives.

5. 5.

   The customer's key driver is nearly always payback. Occasionally this is not money although on examination it is probably the underlying motivation. For example, protecting against repetitive strain injuries is a people friendly policy that can be achieved by automating certain tasks, but, for some, there will be a direct link with contingent liabilities.

6. 6.

   Customers expect equipment to work and need to be aware of all the costs of keeping the equipment working. The customer is interested in a solution that works day in day out and pays its way. This is a major challenge when an environment is so changeable. In our experience reliability is designed in by attention to detail and experience.

7. 7.

   Nearly all robotic solutions are bespoke. The robot may be standard but the ancillary equipment is often just as expensive and made to order. A machine developer is always a systems integrator. The role of a systems integrator is to piece together the complete solutions, using existing reliable components where possible and only resorting to new technology as a last resort.

8. 8.

   Sometimes we start from the wrong place – no-one wants to throw away years of development but sometimes it is just not possible to get to the final goal without binning what has gone before. It is a tough job finding the right vacancy for an enthusiastic, but over-qualified and inexperienced robotic system. This is a big issue for the standard robot manufacturers, where an industrial robot may not be the best solution. Robots are supposed to be flexible but in reality they are not there yet.

9. 9.

   Each unconstrained task has its own set of nightmares. It is possible to develop a common software platform, for user interfaces and control, and to standardise on certain parts of the motion systems, but the handling and sensing requirements will probably be different, along with the required dynamic performance, manipulation range and repeatability.

10. 10.

    Rounded solutions need a team of experts – mechanical design, software, control, production (to name but a few). The final solution will only be as strong as the weakest link – e.g. it is extremely difficult to write software to control flaky hardware.

Thus far this viewpoint has been fairly downbeat, so here are some views on how to make it all work:

1. 1.

   Build strong customer/developer partnerships. The most likely reason for success is a clear need for a solution. This should imply that the customer is driving the development by providing the detailed specifications and investing in the process.

2. 2.

   Build small, strong cross-functional development teams.

3. 3.

   KISS – keep it simple, stupid!

4. 4.

   Focus on the easiest tasks – e.g. although not trivial, handling sausages is much easier than handling deboned chicken.

5. 5.

   Remove as many sensors as possible. Too much information is difficult to manage and does not come for free. Good innovative mechanical engineering and clear thinking can remove issues before they require complex counter-measures – e.g. once you have hold of a product don't let it go.

6. 6.

   When someone demonstrates something that really works – buy it – and if you have enough money buy the company! (They may be able to do it again.)