Better use of resources increases throughput and profit

Making better use of existing resources can help a company increase its manufacturing throughput without any associated increase in overtime or sub-contracted work.

A topic that is increasingly the focus of attention is the optimisation of resources.

Faced with the prospect of a recession, many manufacturers opt to make the best possible use of their existing resources rather than invest in new ones. But this can sometimes be difficult for companies that are manufacturing to order, producing small batches, or making components or assemblies configured to order.

So how can the use of resources, including materials, equipment, operators and skills, be optimised?

The shortsighted approach is to look at each resource and try to optimise its use in isolation. Although this can result in a resource being apparently utilised more fully, it is vital to take a step back and see the broader picture. Resources should not be optimised because there is a feel good factor associated with keeping resources occupied, or that it is important to optimise the use of individual resources.

The true benefit comes from increased throughput without the deployment of extra resources.

It may be possible to schedule work to keep individual resources busy but this may not be the best way to ensure that all current orders are processed as efficiently as possible.

To illustrate this, consider a racing car driving a lap of a track. There is a maximum theoretical speed at which the car can negotiate any given corner, depending on factors such as the radius of the corner, the camber of the track and the grip of the tyres. But there is no point in considering any corner in isolation: a car’s ability to negotiate it will depend just as much upon the sections of track before and after it.

For example, the preceding corner may be so tight and slow that it is impossible to get up to the theoretical maximum speed of the corner being considered. Again, if the car were to come out of the corner at the maximum theoretical speed, it may actually be travelling at too high a speed to negotiate the following corner.

In exactly the same way, the efficiency of the total manufacturing process is far more complex than the efficiency of individual operations; and, in addition, it is important to consider the real-world situation.

This may sound obvious, but it is not that long since manufacturers were happy to accept output from MRP systems that scheduled multiple jobs to start at the same time on the same machine.

Although this approach enables schedulers to begin to plan overtime working and sub-contracting in order to avoid delays, would it not be better not to get into this position in the first place?

Any approach that optimises individual resources without looking at them in the context of the total manufacturing process makes it very easy to fall into the trap of simply moving problems further and further upstream until there is no option but to schedule over-utilisation.

Concurrent scheduling software presents the user with a suggested schedule that is achievable within the given constraints. However, the scheduler can still use his experience and knowledge of the resources, bottlenecks and works orders in order to modify the scheduling.

The software will immediately analyse the implications of the modifications and present the new results. By comparing these various what-if scenarios, the user can quickly see whether it is possible to produce an improved schedule that will optimise the overall throughput, and also the overall usage of the resources.

Looking at individual operations, these may appear to be operating inefficiently. However, as the analogy with the racing car shows, an optimal solution will only be found when all of the operations are considered together.

And ultimately, it is the humans involved who must take the final decision, albeit on the basis of analysis done by software. In other words, for scheduling a series of manufacturing processes, a software package is an invaluable decision-support tool to help the user optimise the use of resources. This will help manufacturers through any real or apparent recession.

Maz Mohamedali is European sales and marketing director for Lilly Software.