How Your Team Lines Up Can Rebalance Your Profitability

March 9, 2009
An unbalanced line can actually outperform a balanced line.

A line where individual workers are free to work at different speeds, passing the partly-assembled parts on to the next station, is called 'unpaced'. In most cases the parts are transferred by hand, while in others some limited form of mechanical assistance is used. Storage space is provided between each station, commonly called a 'buffer,' where the work-in-progress is held until it is needed. The buffer allows the work to continue to flow by eliminating hold-ups in the line, either from a worker being 'starved' of product to process or being 'blocked', by having to hold on to the work he/she has completed until the next operator is ready. So workers can process items relatively independently of each other, a system known as 'asynchronous' production.

'Balanced' vs. 'Unbalanced'? Myths and Modern Thinking

As each part of the assembly process normally requires a different average length of time to complete, unpaced production lines are generally 'unbalanced'. It is often technically impossible to break down the entire job into tasks that each require an equal amount of time to finish, as the nature of the work at each station is different. Also, we must remember that we are dealing with human beings here, and human beings can not be expected to continuously do the same thing throughout their shift at a uniform speed. Indeed, it has been observed that at times an individual's operating speed may slow down by up to 66% from their average rate.

Many serial production line designers and operators believe that unbalancing a production line is wrong. The bulk of operations management textbooks even devote a whole chapter to line balancing and companies all over the world spend a fortune in time and effort trying to balance their lines. Our work raises serious questions about this school of thought. Sufficient research has now been done to demonstrate that an unbalanced line can actually outperform a balanced line.

Research has indicated that where one station is deliberately made slower than the rest -- a 'bottleneck' or 'constraint' station -- this is more efficient, output is higher, than when the line is balanced. In real life, 'bottlenecks' are common to virtually every production line, as the popular 'Theory of Constraints' tells us. According to this theory, the constraint must be identified and given extra resources, and then some real improvements in on-time delivery and more predictable performance emerge.

When we think of the billions of dollars that companies are spending on their production operations, even tiny percentage improvements become financially significant. Let's look in more detail at how the performance of unpaced production lines can be improved.

Small Changes -- Big Savings

We wanted to find out which configuration of worker positioning in the line, from the fastest to the slowest, would produce the greatest improvements in efficiency. We defined efficiency in two ways - reduction in workers' idle time percentage (IT) and reduction in the amount of product lying inactive in the buffers, the average buffer level (ABL).

We ran a series of computer simulations, to observe the behaviour of lines with 5, 8, and 10 stations. In each case, we categorized the workers, based on their average speed of operation, which we call their 'mean service time' (MT), ranging from the slowest to the fastest.

Four configurations were examined:

  1. Placing the fastest worker at the start of the line, followed by progressively slower workers, in ascending order
  2. Placing the fastest worker at the end of the line, preceded by progressively slower workers, in descending order
  3. Placing the fastest worker in the middle, with progressively slower workers on either side (a bowl shaped pattern), and
  4. Placing the slowest worker in the middle, with progressively faster workers on either side (an inverted bowl shape)


IT = idle time percentage
ABL = average buffer level
MT = mean service time or speed of operating
DI = degree of line imbalance
B = buffer size

Degree of line imbalance (DI) means the percentage difference in the amount of time taken between successive workers along the line. So if worker 2 takes 12% longer to complete his task than worker 3, we have a DI of 12%. We identified four degrees of line imbalance: 2% (slight), 5%, 12% and 18% (very high). Buffer sizes (B) were set at 1, 2, 3 and 6 for all the buffers in each line.

Our results reveal some quite surprising data, which can offer fresh insights into improved line efficiency.

In terms of reducing IT, the most efficient pattern was configuration 3, the bowl-shaped pattern, whilst the least effective was configuration 2, where the fastest worker was placed last. The largest improvement over a balanced line was a nearly 3.5% reduction in idle time (for a line having eight stations when B = 1 and DI = 2%). An apparently small figure, but when considered over the life of the line, this can equate to a lot of money in terms of increased output.

We then looked at ABL. Pattern 2, which had performed worst in terms of IT, did best here. The balanced line was outperformed by the best unbalanced line in every one of the line lengths that we tested, as well as each degree of imbalance (DI) and every buffer size (B). The least efficient pattern turned out to be pattern 1, where the fastest worker was placed first. The best pattern produced extraordinary results, cutting the ABL by about 87% (for a 5 station line where B = 6 and DI = 12%) compared to the balanced line. It must be noted, however, that none of the configurations produced simultaneous savings in both IT and ABL.

A number of other findings are interesting to note:

  • It would appear that buffer size and degree of imbalance operate in opposite directions in terms of their effect on IT and ABL. When buffer capacity rises, IT falls but ABL increases, while an increase in DI causes higher IT, but lower ABL.
  • The greater the line length, the greater the consequent rise in IT.
  • When DI is increased, sometimes even to a large degree, IT values pretty close to those achieved in a balanced line can be observed. For example, in the best configuration, with low to moderate buffer sizes (B), DI can be increased to 5%, without causing a significantly higher IT compared to the balanced line.
  • Looking again at IT and ABL, our findings show that it is buffer capacity that has the greatest impact on an unbalanced line.
  • While DI has the biggest influence on IT, its effect on ABL is much less.

There seems little doubt that unbalancing can bring significant performance improvement. But, as with any measured activity, unbalancing has to be done properly, and in the right configuration, or production efficiency will be damaged. And whichever arrangement you choose, there are trade-offs that need to be recognised. If your aim is to increase your line's productive time, you will have to accept an increase in average buffer load (ABL). On the other hand, reducing your ABL carries with it an increase in idle time (IT).

Each manager will have his or her own priorities. It will depend on your industry and your type of operation. In demand-heavy, labour-intensive sectors, the relative cost of idle time is more important than the storage cost of inventory and you will base your decisions around the IT rate. If lean buffering and shorter production lead times are your key measures, ABL will dictate your strategy.

Traditionally, there has been little understanding of the effects of allocating workers who operate at different speeds. Too often individual workers are placed at their stations for pragmatic reasons. Now it makes sense, since most lines are unbalanced anyway, to unbalance your line more scientifically. But remember, reductions in IT and ABL don't require any costly changes to the line itself, just putting the right workers in the right places.

They say that the business climate is not going to improve greatly for some time. We hope that we have provided some ideas that will improve your team's game and produce the financial benefits that help your operation to survive the storm.

Dr. Sabry Shaaban is an Associate Professor, and Simon Lawder is a Visiting Professor, ESC Rennes School of Business in Rennes, France

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