Typeset

Agile methods are extremely useful in solving complex problems. This is particularly beneficial in market environments where the routines of traditional corporate management are constantly being questioned. Agility is closely linked to the core ideas of Lean Management, as evidenced by the focus on processes and people. Lean factories facilitate a hands-on engagement with Lean principles, thereby promoting agile process management in various production contexts.

In the context of Industry 4.0, learning factories are important places for company-based learning. Studies show that they have continued to develop since their emergence and are no longer limited to vocational and academic education. This leads to the question of how much the concept of the learning factory represents an innovative approach to further training in small and medium-sized enterprises (SMEs). This article focuses on three selected learning factories relevant to continuing education that were analyzed using qualitative methods with regard to their concepts and cooperation. The findings are embedded in a theoretical framework that links the scientific discussion on learning locations and educational cooperation. The empirical findings from three learning factories illustrate relevant learning locations for continuing education in SMEs.

The success of technologies depends not only on their innovative strength and acceptance, but also on their management. Decision-makers evaluate factors like technical framework conditions and organizational requirements, with the demand for flexibility adding to the complexity. Industry 4.0 addresses this with networking, transparency and decentralized decisions. Digital twins, which can be implemented with open source software, play a key role.

The typical problems of a medium-sized company, coupled with the new requirements for sustainability, harbor the potential for economic tension. Learning factories can counteract this: they simulate production processes and offer an environment where participants can develop knowledge and skills in a realistic production setting. Establishing an innovation factory not only increases productivity, but also significantly reduces land consumption.

Digitalization opens up new forms of operational training. A growing focus is on smart services, which allow for proactive engagement with customer demands and empower businesses in times of digitalization. While traditional learning environments are rarely tailored toward individual needs, smart services offer new opportunities. Decentralization, previously only a utopic vision, is becoming the reality now.

In remanufacturing, used goods are brought up to the quality level of a new product. This distinguishes it from recycling, which recovers materials and converts them into new units or products. Various uncertainties, such as the condition, quantity and time of return, can be minimized with Industry 4.0 approaches and artificial intelligence. A special learning concept ensures that employees have the required competence profiles in this context.

The volatility of economic conditions and rapid technological progress require production sites to be constantly adapted and improved. This needs highly qualified factory planners who can use digital planning tools efficiently. The best qualifications emerge from closely interlinking the teaching of planning methods and the application of these methods in a planning project according to the principle of “learning by doing”.

Learning factories promote digital transformation through an interdisciplinary approach between lean management, Industry 4.0, energy efficiency, training center or research farm. SME centers are characterized by the on-site integration of small and medium-sized companies. Such a regional strategy, combined with learning factories, promotes a goal-oriented dialog between science and practice where students can put their theoretical knowledge to the test.

Short delivery times are essential in competitive markets. In addition to product selection and quality requirements, customers are also demanding more and more from logistics. However, high product variance complicates the situation, as it involves complex material flows and therefore leads to long throughput times. However, a four-step process analysis and modeling can help to reduce throughput times and strengthen the competitiveness of companies from within.