Can packing planning algorithms support kitting?

Kitting, in its most basic sense, means bundling up individual products into ready-made sets. It is grouping very different products, which when put together, will create a new one, in one container. You can see at first glance that this process can be effectively optimised using packing planning algorithms.

Kitting is a well-known strategy that is used in production supply processes. However, it can be extended to all situations in which it is necessary to collect the parts that make up a new product, order or set. If you have IKEA furniture at home, you will quickly understand what kitting is.

What is kitting?

Kitting, in the manufacturing process, means preparing sets of components, which in the next stage are delivered to the assembly line. Such organisation of production and the material flow results from the need for optimisation, i.e. in this case the desire to minimise the assembly time of the finished product. It turns out that separating collection of the components from the assembly process may result not only in speeding up production, but also in an increase in its quality.

Completed sets can go directly to manufacturing cells (to buffers at assembly stations) or to a warehouse. In this way, it is possible to prepare an appropriate number of ready-made assembly kits in advance, which will ensure that production is secured (in this case, its continuity).

Challenges in component kitting

To prepare a kit, it is not enough just to put all the parts in a box or a container. They have to be arranged in such a way so that they can be taken from the container at the assembly station in the strictly defined order in which they will be used for assembly. A chaotically completed kit causes a huge loss of time and significantly reduces  production efficiency.

Kitting is difficult to automate as there is a wide variety of combinations of sets, due to, among other things, the need to differentiate and customise finished products. A very good example is manufacturing pens – the number of parts is small, but the variety of their colours, forms and materials make an impressive number of possible combinations.

Picking is done manually by pickers who have to arrange parts in the proper way in collective containers. If the kit is going straight to the assembly line, the packing problem is solved by a large container. It should only be as big as the largest possible combination of components in the kit (in terms of dimensions, not quantity). The problem begins when you need to prepare kits for stock or for transport. In both cases, you have to bear in mind the space factor – both in the warehouse or in the cargo space of the means of transport. And this is where you not only need to, but can, automate the packing planning processes.

How does the packing planning system support kitting?

A kit that is to be stored or transported requires careful protection: against mechanical damage, weather conditions or loss of its parts. Therefore, all components should be carefully packaged before being put in a collective container. This means nothing less than you having to determine the volume of the entire set and adjusting the appropriate collective container. However, every change in the set of components may result in the need to recalculate the volume of the entire load (sometimes one change of a part for another of a different size). The process is time-consuming and exposed to a high risk of errors. That is why many companies try to avoid problems using a large container and a large amount of fillers. However, this is not an eco-friendly solution, and first of all – very expensive. You have to ship the same container which is sometimes 70% full, sometimes 50% full, and the cost of shipping is the same. You’d be better off introducing a much better economic solution – using packing planning algorithms.

In the case of kitting, the Container adjustment algorithm will be optimal. It allows you to quickly check which of the packages you have in stock will be the best for your kit (fits the size of your set in an optimal way). If you are going to order or to produce the packaging, you can precisely define its dimensions. In this way you may minimise the usage of fillers as the algorithm allows the maximum use of space. You can apply this algorithm to any kind of storage space like a transport trolley, a container, on a shelf or in a delivery truck.

By using the Container adjustment algorithm when kitting, you may optimise the use of cargo and warehouse space, shorten the collection time, increase the flexibility of the supply chain and minimise the risk of errors. In terms of production profitability, this means, respectively: optimisation of transport and storage costs, lower labour costs and a lower risk of production interruptions. You can check out today how our algorithms work: a free demo is at your disposal.