The global household appliance industry is in the process of digital transformation, both because the household appliances themselves must evolve to meet the expectations of consumers, and because the production plants are under great pressure to maintain their competitiveness. If we add to this trend the latest mergers and acquisitions among manufacturers to set up stronger industrial groups, we could say that the sector is on the verge of undergoing a transformation of its business model.
White household appliances are undergoing major changes aimed at improving energy efficiency, as well as design and connectivity. Among the most noteworthy, we could mention the use of functional surfaces on the visible parts (waterproof and anti-fingerprint coatings), as well as designs which are generally becoming more complex in terms of geometry which comprise more difficult materials to process.
In this context of tough competition, companies seek to reduce costs by taking advantage of economies of scale, to pursue the differentiation of their products, the development of new products and try to enhance after-sales assistance as a way to attract and retain customers.
If we analyse the trends of the sector we can identify challenges related to processes and materials among which we can highlight:
- Stainless steels with coatings
- Folding and control of the elastic recovery of the material
- Process control in terms of the dimensional quality of pieces
- Adaptability and flexibility of the means of production
- Processes equipped with sensor systems
KONIKER makes available to the white goods sector their knowledge in the development of processes and productive means capable of satisfying the need for changes in models and materials, all aligned with the application of new technologies within the industry 4.0 paradigm
Among KONIKER’s research lines, we can highlight those developed with the raw material manufacturers to evaluate the technical-economic viability of their processing (cutting, bending, punching, profiling, joining), as well as research aimed at obtaining intelligent machines that also have a high degree of automation which is capable of adapting and of self-learning to maintain optimum quality levels.
- Transfer and automation
- Process control