Green Production Planning - Resource-efficient And Sustainable Production

by Stipo Nad
Eco friendly industry concept. 3d rendering of green factory icon on fresh spring meadow with blue sky in background.
(c) Petmal - Getty Images

Due to high CO2 emissions, many industries are coming under increasing pressure to reduce their emissions. The machine and system engineering sector is also increasingly feeling this demand. But reducing emissions can also be an opportunity for this traditional sector. After all, according to a study by the German machinery and plant manufacturing association (VDMA) and the Boston Consulting Group, it can generate an additional 10 trillion Euros worldwide by 2050 with climate-friendly technologies such as electric motors, recycling plants or wind turbines. Hartmut Rauen, Vice Managing Director of the VDMA and co-author of the study, estimates that 86 percent of the emissions of the world's 36 largest countries can be saved with the help of technologies from the machine and system engineering industry. That is around 30 gigatons of CO₂ per annum.

However, there is also still potential for green processes among the machine and system manufacturers themselves. There are also many opportunities for the traditional industry to produce in a more resource-efficient and sustainable way.

Sustainability through agile optimization in production

The waste of resources in production offers many opportunities to increase the sustainability of processes. Quite often, unreliable and unrealistic planning still leads to inefficiencies in manufacturing processes here. But there are already proven solutions to eliminate these. Digital planning systems that plan against limited, realistic capacities and resources make it possible to create on-time material supply along the entire supply chain and improve production efficiency. These systems help in production planning through agile optimization based on intelligent algorithms to avoid resource waiting times and reduce inventory while maintaining production output.

Added to this is the avoidance of "reactive power" in the manufacturing process. This means, for example, that special measures such as additional shifts are used at the weekend, although the material produced then remains unused for weeks because the parts that are also needed for the next processing step arrive late in parallel.

A real-life example shows another effect of inefficient production planning: One of our customers from China was often forced to deliver its shipments to Europe by air freight due to inaccurate planning, as sea freight deadlines could often not be met due to schedule discrepancies. This resulted in high costs for the machine and system manufacturer - and high CO2 emissions for the environment.

Intelligent planning and agile optimization can counteract these negative effects on efficiency in the company and on the environment by creating maximum adherence to schedules and planning resources, such as materials and machines, intelligently.

The prerequisites for sustainable production are in place

Machine and system engineering has an advantage: In most cases, all the prerequisites for planning sustainable production are already in place. The complexity of the products as well as the high number of orders lead to immense amounts of data, which ERP systems are well suited for collecting data, but not for realistic and agile production planning and control. Thie planning is still often done by hand and paper. However, this often leads to the fact that the respective departments focus locally on their areas, the company-wide view of all processes is missing. The result: despite high-capacity utilization in the production areas, there are long lists of missing parts in the assembly department. This waste logically does not lead to an overall optimum in the company. Therefore, upstream and downstream as well as cross-departmental processes should also be taken into account. Only in this way can a company-wide efficiency optimum be achieved.

Methods based on artificial intelligence (AI) help here to optimize the complex processes across the board as an overall concept and to be able to produce efficiently accordingly.

Conclusion

It is high time to reduce emissions across all industries. On one hand, machine and system engineering can exploit great economic potential by developing new products that promote environmental protection. On the other hand, the industry must also rethink its own processes and eliminate inefficiencies in order to become more CO2-neutral. There is no way around digitalization here: Intelligent systems help to plan processes holistically in such a way that production and delivery can be carried out in a resource-conserving, sustainable and on-time manner.

What inefficient processes are you struggling with in your company? Do you already use intelligent systems for better planning and control of production processes?



You may also like

Using Artificial Intelligence in the Fight Against Money Laundering and Terrorist Financing

Read

Sustainable logistics at airports – Is it possible?

Read

Green Logistics - How to make your transports (environmentally) efficient

Read

About the author

  • Stipo Nad

    Stipo Nad started working for INFORM in 2001. He is interested in all topics related to Advanced Planning & Scheduling, Production Planning, Business Intelligence and Industry 4.0.

    All posts by this author

    More about the author at:

Our authors

Find all our authors at a glance!

All authors

Back to top