Inform with Five Steps for Efficient Production Logistics

The software manufacturer Inform GmbH presents five points for improving production logistics. Companies still have a lot of potential in optimizing the interface between logistics and production. Inform assists with the development of corresponding software based on artificial intelligence and operations research.

(Aachen) Logistics and production are often still conceptually separated. However, this does not lead to success, argues the Aachen optimization specialist Inform. With the following five steps, companies can achieve an efficient interplay between these two central areas.

Companies still too rarely recognize the unnecessary problems that hinder their work in intralogistics. While just-in-time concepts were previously almost exclusively used by automobile manufacturers, many medium-sized manufacturers have caught up in recent years: Sophisticated processes with modern technologies ensure as much flexibility and stability in production as possible, which should absorb volatile demands and consider individualized customer wishes. Logistics organized on sight and call can no longer keep up; the tasks are too comprehensive and complex. Inform has identified five crucial measures to make production logistics more efficient.

Five Measures for Efficient Production Logistics

1. Cooperation on Equal Terms

The first, but perhaps also the hardest step is to establish communication on equal terms between logistics and production. If this is not given, even extensive investments in technology often do not lead to the desired results. A culture of collaboration is needed.

It is the task of logistics to engage in conversation with production, understand its needs, and agree on internal service-level agreements to meet these needs. On the other hand, production – often preferred as the core of a manufacturing company – is still dependent on logistics even when a lot of money has been invested in improving manufacturing processes.

As fewer and fewer storage areas are available directly near production, the transport of materials and containers must be efficient. Therefore, production should also become more transparent for logistics and refrain from spontaneous order placements on call.

2. Optimization Algorithms

Not knowing where forklifts, materials, empty containers, or other resources are located within the company is a common reason for implementing an advanced transport control system. The need for transparency is justified, but it only helps dispatchers under time pressure to a limited extent, as there are often numerous tasks at hand with only limited resources available. For just ten possible transport orders, there are around 3.6 million possible sequences to process.

For this reason, a transport control system must not rely solely on transparency. It requires intelligent optimization algorithms that can derive ad-hoc from the specific situation which forklifts, trains, or automated guided vehicles (AGVs) should carry out which order next. This way, the transport control system creates the best possible matching of orders and resources and optimally serves the order network as a whole.

Newly created orders are immediately incorporated into the overall planning with the help of optimization algorithms. Thus, a suitable follow-up order or appropriate order combinations are calculated for each active and available resource in seconds.

3. Planning Ahead

However, the complexity of production environments is increasing. Medium-sized companies are also implementing lean management methods or establishing manufacturing facilities that could flexibly carry out various production processes. The more flexible the production with its daily demands, the more complex and relevant for success logistics becomes.

In this context, it is important to incorporate future aspects and consider processes as long-term as possible. There is no crystal ball, so the goal is to make the unplannable as plannable as possible. Instead of generating transport orders in an ERP system only in the short term and transferring them to the transport control system, processes should be established that allow for demand forecasting several days in advance. This way, resources and employee deployment plans can be planned according to demand. Such planning processes can be supported by transport control systems by simulating tomorrow’s needs.

4. Utilizing Existing Data

A common obstacle is that companies underestimate the quality of their data. Often, enough data of sufficient quality is already available, scattered across many different systems, but it needs to be structured and consolidated so that a transport control system can plan with the appropriate lead time and incorporate this planning into optimization. After all, logistics should not just put out fires but contribute to punctuality and delivery speed of production with stable processes.

5. Machine Learning

Once the first steps have been mastered, one can consider further examining the now holistically viewed data using machine learning algorithms. This makes correlations in the data flood visible that escape human perspective. By considering various data from different sources, for example, seasonalities or order combinations could be discovered, whose processing is particularly easy or particularly difficult. This insight can then be used to further improve one’s processes.
“Right now, it is important not to simply invest in a hype,” says Matthias Wurst, Head of Business Development Industrial Logistics at Inform. “We believe that digitalization projects should be checked to see if they contribute to exactly the goals one wants to achieve. Sometimes, new paths must be taken, and the synergies between production and internal logistics must be uncovered and exploited to achieve more efficiency and resilience for the company as a whole.”

Inform GmbH

Inform develops software to optimize business processes through digital decision-making based on artificial intelligence and operations research. It complements traditional IT systems and increases the profitability and resilience of many companies. While data-managing software only provides information, Inform systems can analyze large amounts of data in seconds, calculate numerous decision variants, and propose the best possible solution for implementation. More than 750 software engineers, data analysts, and consultants currently support over 1,000 customers worldwide in industry, trade, airports, ports, logistics, banking, and insurance. Optimization includes sales planning, production planning, personnel deployment, logistics and transport, inventory management, supply chain management, as well as fraud prevention in insurance and payment transactions.

Photo: © Inform

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