In the Coronavirus Crisis, Planning Reliability is Gone - How Can Production Planning React?
03/19/2020 Stipo Nad
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Currently, the coronavirus is causing uncertainty across all areas. This has a significant impact on the planning of events, for example, most events in the near future have already been cancelled, and schools and kindergartens are closed. The effects of the virus are also increasingly being felt in machine and systems engineering. In addition to the already widespread planning uncertainty in production planning, there is now a further, serious disruptive factor. It is currently still difficult to estimate the exact effects this will have.
According to the German Mechanical Engineering Industry Association VDMA, however, the effects of the coronavirus crisis will be clearly reflected in the order figures in the coming months. According to a survey by the ifo Institute, the consequences of the pandemic will be felt most in the machine engineering industry, alongside the electrical and chemical industries.
What are the current challenges?
A major challenge in machine and systems engineering is currently the supply of primary products or raw materials. As a result, production has slowed down dramatically and even in some cases stopped indefinitely.
The loss or planning of employees is a major challenge for the industry - even before the coronavirus spread. Many companies have been struggling with under-utilization for months and urgently need a practical solution to extend short time working, which has now become all the more urgent due to the pandemic. Intelligent capacity requirements planning, which can also be used to plan short time work, is therefore becoming increasingly important.
Making a start
Now it is useless to look back and ask "what if". It is more important to learn from the current crisis and to be well prepared for the future. This applies not only to disruptions on the scale of a pandemic, but also, of course, to the many, much smaller disruptions that companies face even in calmer times.
Disruptive planning factors are a daily challenge in machine and systems engineering, but it is by no means impossible to react to them quickly. In order to detect disruptions at an early stage, it is first necessary to analyze the current status. Due to complex planning processes, the high number of orders and a lack of transparency, an extreme effort of coordination is necessary, because all departments involved in the process, from construction, purchasing and sales to assembly, are also involved in production planning. The result is an enormous time expenditure and consequently high costs. In addition, employees are often dissatisfied because new disruptions, such as employee and machine downtimes or delivery delays, mean that time-consuming coordination is followed by new meetings. The lack of transparency in all production processes means that employees can only react to disruptions, not act proactively.
Digital planning instead of flying blind
Digital planning can counteract these challenges by first creating transparency about the current situation in production and up- and downstream processes. This cross-divisional order network enables possible disruptive factors across all relevant processes to be identified at an early stage and countermeasures to be initiated. The lengthy exchange of information in time-consuming meetings is no longer necessary, as an up-to-date, cross-departmental level of information is guaranteed.
For example, every department can see which order is at risk in terms of deadlines, so that countermeasures such as additional shifts or extended working hours can be initiated in good time. By displaying all orders as a collective order, APS systems also make it clear what relationships exist between the individual orders and what effects, for example, the delay of one order has on other orders.
In the event of unexpected disruptions, the system must be able to respond to the new situation in an agile manner. If something unexpected happens (for example, material is unusable or delayed, or the machine malfunctions), all the work affected by this must be postponed. However, the capacities originally planned for this will also be released. What needs to be evaluated and changed manually before using an APS system is now automatically recorded and dynamically integrated into planning. In this agile optimization, the freed capacities are then used intelligently - for example, to "save" as many other appointments as possible, which may have been postponed even by earlier disruptions. In this way, the optimum solution is always achieved from the available capacities - automatically, with minimum effort.
The coronavirus pandemic has far-reaching consequences for the economy. The machine and plant engineering industry is also severely affected. At present, the exact impact of the coronavirus on machine and plant engineering is still difficult to assess. Therefore, a comprehensive solution to the individual problems in the company is still some way off in the future. Intelligent planning is often required to contain the effects of disruptions. Intelligent capacity requirements planning helps to better plan measures, such as short time work, and thus to make optimum use of the available resources. An APS system can also help to maintain an overview of orders and reduce the potential effects of disruption. With the help of software, all orders and deadlines can be scheduled in such a way that despite bottlenecks and rescheduling, the optimum solution is still achieved in planning.