Stocking up – getting ahead of orders

 Artificial intelligence can help manufacturers to restock consumable items such as PPE, lubricants and bearings with greater speed, accuracy and efficiency, writes Patrik Grönman, CRIBWISE Development Manager

Re-ordering stock in an accurate, timely manner is critical to the smooth running of any machine shop. Every type of consumable is potentially critical to operations. The sudden lack of a bearing, for instance, can lead to unexpected machine shutdown.

As Benjamin Franklin put it: “For the want of a nail, the [horse]shoe was lost.”

Managing stock levels is still a challenge in modern machine shops. This is especially true in those that still rely on tooling catalogues and other paper-based systems. Even those that have moved online could make improvements, as replacement orders are typically made on a case-by-case basis. The accelerating pace of manufacturing makes the job of restocking consumables more complex and challenging than ever.


As in many other aspects of engineering, digital technology will help to drive improvement. In this case, the answer comes from a surprising source: artificial intelligence (AI) – which is more commonly associated with robotics.

We have incorporated AI into our tooling inventory management software, helping to improve stock optimization on the shop floor. Our company’s mission is to help job shops get control over their tooling-related inventory and related purchasing processes – and so maximise production efficiency.

The AI functionality – called Stock Optimization – minimises the time and effort that users need to spend maintaining optimum stock levels. It can deliver equivalent – or better – optimisation than most experienced users can achieve manually.

AI learns by ‘recognising’ certain conditions without the need for specific programming. This means it can interpret inputs and act on them – rather than needing to hit a set level or respond to an alarm, for instance. In this way, it actually learns on the job – and so improves its performance over time.

Input values

The main function of Stock Optimization is to optimise the order point – and order levels – of consumables, based on historical consumption and purchase lead times. It fits seamlessly into our broader optimization offering – which, for example, classifies consumables into three different ‘classes’ (A, B and C). Here, ‘A’ items need more frequent replacement.

The software uses advanced algorithms to track and analyse data. It is based on four key input values: training period; service level; order frequency; and whether or not to include safety stock.

  • Training period: the initial step needed to ‘teach’ the system;
  • Service level: expressed as a percentage of stock availability at any time;
  • Safety stock: extra items on hand to bridge the gap of delivery inconsistencies; and,
  • Order frequency: as in ‘how often’, and what is the timing between orders?

There are only a few basic criteria for using it. Ordered items must be consumables; they must be bought through our purchase function; and a minimum 30-day measurement period is required, with at least 15 picks.

Key benefits of Stock Optimization

The main advantage is simple: it reduces manual work. Purchasing and stock responsibility – which would otherwise require manual change order parameters on anything from 500 to 1500 items – are now largely automated.

As the name suggests, it also optimizes stock levels. This reduces the capital tied up in tools and PPE, by suggesting correct order parameters. In addition, it increases the rate of inventory turnover – and takes the guesswork out of tool inventory management.

Despite its futuristic nature, the software is already being used. Valmet, which produces machinery for the pulp, paper and energy industries, has begun using Stock Optimization in two of its departments – including a machine shop. The software has helped it to reduce the time involved in purchasing and receiving, while also cutting the cost of stock ownership in everything from PPE to tooling.

Re-ordering stock is a tedious – through necessary – part of manufacturing. Efficient stock optimization can help manufacturers streamline this critical but time-consuming part of their operation.

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