Laundry production isn’t sexy
Without the people and the market, the laundry is just a building with a potential. But there has always been something special about the working conditions in a laundry.
Let us, just this once, put it the way it is: Laundries have been warm as hell, damp as a Finnish sauna, mucky, with an infernal noise of leaking air valves, spinning washer extractors and screeching breaks. The workers drank water every hour, ate salt tablets, and was tied to a single, poorly equipped workstation, carrying out a heavy, monotonous, exhausting work, all day long, that practically didn’t require any preceding knowledge of anything. Arms and legs, and not that much more.
When recruiting new personnel one half dropped out within the first two weeks, usually because of overload injuries – unless the recruiter was able to pinpoint the tough ones. And the tough ones weren’t the BAs, the BComs or the MScs. The tough ones were women, sweating, smoking and spitting like men, with hair in their armpits, cursing, most often in a language you didn’t understand, slapping you in the face if you got to fresh with them.
But when that is said, the industry is also changing. Today we have modern, industrial laundries – with well-equipped workstations, modern management principles, good working environments and educated, committed employees – even though we still have to fight a reputation that reaches out from years back. The old, out-of-date laundries disappear, sometimes into larger laundry groups, with staff functions, specialized production units and a willingness to invest in the future.
Slowly the working and management conditions in the laundries begin to resemble other, comparable industries. Slowly the running of a laundry is rising up from the traditional preconception of the trade, to find its place in a modern, technological society.
A sexy industry?
But the general conception of the laundries has even rubbed off onto the industry’s suppliers.
Put bluntly: It is not a sexy industry to be employed in, or to be a supplier to, the same way it is to supply the car or aircraft industries. The smell in the laundry leaves us, to some extent, alone by other rival industries.
And then again not. We see it with the laundry and supplier groups quoted on a stock exchange. Stock prices are low. Not because the laundry or its suppliers are earning less, or not performing as well as their colleagues in other industries, but because there is more appeal to owning a stock in a software, computer or medical company. It’s cool in a way we cannot match. Yet.
What the laundries and their suppliers lose by are not earnings, but the subtler elements of valuation – as the difference in the pricing of two paintings. A Picasso just sounds better than a Capisso.
But if we are to make the industry more appealing, we only have the jobs, the working conditions, the technology and our ability to run the companies to do it with – our earning powers.
The flow of goods
So when we, the managers, look out over the production, the clothes in the check-in, the trimmed machines, the trained employees and the customers eagerly waiting in the dispatch department, what means of influence on the company’s earning powers do we actually have?
Not a lot – and yet…
In the short term the laundry’s earning powers depend alone on the flow of goods through the production, keen production methods and clever organization of the work. And since production methods and techniques focus on controlling the flow of goods, and since clever organization also depends on the flow of goods, in the short term that is what it is all about – controlling the flow of goods. During the working day that is simply all we are left with.
On the other hand the choices made in the short term have great impact on a majority of the costs – because they by definition constitute the total variable costs, some 70% of a laundry’s cost complex.
Short-term variables
So how do we control the flow of goods? What are our options?
Not many. Production methods and material flow control come down to no more than four parameters:
• the number of batches in a planning lot,
• the lot’s batch sequence,
• each batch’s route down the laundry production (the process route), and
• the allocation of employees to the workstations.
But these choices are made all the time. Day in and day out. And here is my point: If these choices are based on misconceptions or lack of knowledge, experience or insight, it may have fatal consequences to the laundry’s economy.
This is the secret behind all – and I really mean each and every – successful production, because of the simple fact, that in the accounts a pound sterling of costs weighs more than a pound sterling of turn-over.
And I am not talking about a little, but more than 5 to 10 times more.
Permutations
When picking a number of batches for production, e.g. 10 batches of different categories, these 10 batches may be arranged and sent into the production in: 10 x 9 x 8 … x 1 = 3,628,800 different sequences (not counting alternative process routes).
If you instead pick some 20, 30 or 50 batches, the number of different sequences becomes incomprehensible. And so here’s is another point:
Not all, but a great number of these sequences cause their own, unique consequences in the production, each with their own, unique consequences in the accounts.
One sequence may cause an average water consumption of perhaps 7.3 litres per kilogram clothes, where another sequence, which because of incompatibility requires bath exchanges on the CBW, may cause a water consumption of 8.8 litres. One sequence may result in an employee productivity of 61.2 kilogram clothes per employee hour, where another sequence which causes waits and empty buffers results in a productivity of 58.2 kg.
In a diagram with all possible sequences of the 10 different batches shown, the consequences may look like the curves in the figures below.
The lessons
If the laundry seeks to fulfil a financial goal, one batch sequence achieves this better than the others. In the example one batch sequence results in the lowest total variable costs, without neglecting deadlines.
Had the laundry’s objective been shortest possible lead-time, one of the batch sequences would have fulfilled this better than the others. And it probably wouldn’t have been the same.
We can learn two lessons from this:
• different batch sequences result in different solutions, with different consequences for economy and lead-time. Since the sequence choices are made by people, who most often chose from different motives and with different skills, the laundry see varying results in the production, depending on the planner in charge. But the laundry does not want different, person-dependent results of its production. The owners and the management want the best solution, every time, no matter who makes the decisions,
• you cannot calculate all possible sequences and their consequences. There are simply too many. Had we had a powerful computer, which was able to make 100 calculations per second, it would still take 10 hours to calculate the consequences of 3.6 mill. solutions. 10 hours from now the employees have gone home, the customer has found another laundry that is able to deliver, and our laundry would be out of business.
The bag jockeys and their motives
By deciding which batches to send into the production, their sequences and their process routes, the laundry has indirectly decided what workstations are to be manned, and when.
And often it is indirectly in more than one sense, because only a few operation managers make these decisions with the aim to manage and control the production.
Most operation managers have other purposes in mind, such as:
• emptying the check-in,
• finding certain categories required by the dispatch department,
• maintaining a low water consumption,
• avoiding jamming of the tumble dryers,
– or something completely different, which we don’t always know what is.
Often the person responsible for the selection of batches for production (the Americans call them bag jockeys) is not the same person responsible for the allocation of employees to the workstations. An overall planning of the entire production seldom takes place. More often planning takes the form of habits, conventions and culture, because the lack of planning as an active forward pointing action may be substituted by habit. You just do what you’ve always done, and this may be all the planning that takes place.
But this is wrong.
One cannot not-plan. But there is a major difference between making random plans and making plans aimed a specific targets and at fulfilling specific objectives. We cannot afford stops, waiting for supplies or to produce goods not demanded by the market. It is only when the flow of goods runs free and unrestrained through the production that we are able to keep down the operating costs.
Which leads to the next point: The flow of goods determines the allocation of resources – it is not the allocation of resources that should determine the flow of goods.
And if the allocation of resources are dictated by the flow of goods this also implies that we should not let machines or workstations run, just to keep them running. It is okay to let machines, also the ones that cost a fortune, stand still.
Process route interactions
But why? Shouldn’t we keep the expensive machines running all the time?
No, please. Things interact. One workstation is supplied by other workstations upstream, and itself supplies workstations downstream. If we are to keep a machine running just because it is new and has cost a war, we also keep all other workstations along the process route running, upstream as well as downstream.
If we keep the expensive machine running producing categories not demanded right now, we steal time and capacity from the entire process route. And some of the workstations along a process route are also part of other process routes, for instance the check-in and dispatch departments. Soon the entire laundry is occupied – making stuff nobody needs right now. Also the bottlenecks.
Not good. The flow of goods must adapt to the market demands. Not to the capacities.
Interactions between planning areas
And there are more interactions we have to respect.
We would like to send batch categories into the production in a way that fits the available capacities. Spread full dry work over the entire week. Make sure to have a good mix of full and predryed work every day – a good product mix. In this way it is easier to get all the goods through the production.
But this requires the distribution – to some extent – to adjust to the production. Which is only possible if the supplies with the customers are adjusted to the delivery and collection intervals, which means we have to adjust customer stocks to the distribution.
In this way the wish for a good product mix in the production determines collection intervals and places. Collection intervals determine customer stocks, and the actual collected quantities determine the actual product mix. The loop is closed at a level that (hopefully) corresponds to the capacity of the production equipment.
In this way there is a direct link between production optimization, distribution optimization and inventory optimization – and back to the production again. None of the decisions made within these optimization areas avoid influencing the other two. And send repercussions back to the first again.
Fluctuations in a closed system
Thought-provoking. And with very tangible effects. The consequences of the planners’ decisions fluctuate through this closed system, and the closer the system is to 100% utilization, the higher the waves get. Mathematically the effect is denoted:
In a linear dependency between two or more variables, fluctuations vary around the maximum deviation. The shit selfperpetuates, so to speak – and gets worse and worse. Steals power from the system, locks capacities and restricts our responsiveness and our access to the market. The faster we run, the farther we get from our goals.
And in such a system, where everything interacts, how do we calculate capacities?
What is capacity?
For a machine, a process route or the entire laundry?
A machine’s capacity is actually not interesting, when it is the flow of goods through the laundry that governs the costs, and when it doesn’t help us to have a machine making 1100 pieces an hour if upstream and downstream workstations only make 800. The definition of capacity must reflect this fact.
With regards to planning, capacity is flow capacity, which is process route capacity, which is:
a combination of:
• fill levels,
• the way workstations are connected in process routes,
• the product mix on the process route,
• the batch sequence down the process route, and
• the capacity of the individual workstation (if it is a bottle neck).
Not the easiest definition to remember, but an adequate and usable one because it tells us a lot – for instance how to increase capacity in a number of different ways. We now know it can be done by:
• increasing the capacity of a single workstation (if it is a bottle neck),
• increasing fill levels on bottle necks (machine, category or distribution trimming),
• changing the process routes (steer free of bottle necks),
• changing the product mix, or some times simply by…
• changing the batch sequences.
Surprisingly enough only one of them has to do with the workstation’s individual capacity. Most of them have to do with the way we organize the work and the flow of goods.
The definition also tells us that capacities are dynamic and depend upon the planning, which actually means we can’t tell anything about the capacity of a given process route until we know the specific product mix and the batch sequences.
The point is: Capacity is closely attached to planning.
Proportioning the capacity of a workstation necessarily has to take into consideration workstations upstream and downstream, and the planning routines. We know that now.
Then what is a bottleneck?
The transition from large to small diameter. From wide to narrow. From more to less capacity.
You could of course have proportioned your production equipment in such a way that all upstream workstations have more capacity than workstations downstream – does that turn all the workstations into bottle necks?
No. If a workstation only runs for a very short period (e.g. 2 minutes) of a working shift or a plan, it really doesn’t make any sense to call it a bottleneck. The bottleneck is the workstation with the greatest bearing on the overall capacity.
On the other hand, if all downstream workstations have more capacity than workstations upstream does that mean there are no bottlenecks?
No. There is always a workstation with greater influence on the total process route capacity than the others.
Then for a batch lot the bottleneck must be:
• the workstation whose marginal change of process speed has the greatest absolute bearing on the total lead-time along a process route.
I know. These definitions are not the easiest ones to remember, and they may sound a little academic, but they do have some hard and practical implications. And here is the simple shortcut to the identification of the bottleneck:
• the bottleneck is the workstation that – during a plan – operates the longest time.
And no, you cannot do away with the bottlenecks. There will always be a bottleneck. And they are neither “evil” nor “good”. They are just a fact we have to devote more attention to, when we plan.
What is consumption?
With these definitions of capacity and bottlenecks we see that lead-time (the time from the first batch of a lot leaves the check-in until the last batch of the lot enters the dispatch) depends on planning. Does that apply to all kinds of consumption? What is consumption?
Not so much different from the definition of capacity.
With regards to planning, consumption is process route consumption, which is a combination of:
• fill levels,
• the way workstations are connected in process routes,
• the product mix down the process route,
• the batch sequence down the process route, and
• each single batch’s independent and dependent consumption on each workstation.
Independent consumption does not, as the name indicates, vary with the planning. A typical independent consumption is the fresh water consumption on an old-fashioned washer extractor.
A typical dependent consumption is the fresh water consumption on a continuous batch washer (CBW) washing incompatible categories requiring bath exchanges or empty compartments inserted.
Flexibility and lead-time
Specialisation has improved capacity and process speeds on each single workstation and total lead-times in the laundry, but flexibility has a different and more profound influence on the utilization of capacities.
A simple example: If more (e.g. 30) people of different sexes have to go to the lavatory at the same time, the problem is most often easier and faster solved with access to 3 unisex lavatories, than with access to 1 lavatory for gentlemen, 1 for ladies and 1 for the disabled.
This is a simple mathematical fact.
If we bring this knowledge into a laundry context it is easy to understand that the more work-stations each employee is able to operate, the easier it is to plan and carry out the production.
This also applies to machines, of course. The more different categories a working station is able to process, the easier it is to get the batches through the production. Flexibility increases material flow capacity and brings down the total lead-time in the laundry.
This was some of the most important preconditions of laundry production. In the coming articles I will present methods how to best handle the laundry production under these given conditions.
Hans arbejde er baseret på års erfaring med virksomhedsdrift og ‑planlægning på mange niveauer, både i produktions-, service- og udviklingsvirksomheder (bl.a. 8 års erfaring som vaskeridirektør).