Analytics

Customers are increasingly demanding electronic components with high quality, which forces companies to continuously fulfil these requirements. This leads to a high number of inspection gates with high inspection severity and a high number of pseudo defects. Double inspections by process experts reduce these defects but generate high inspection costs. Autonomously acting inspection systems meet this challenge. Within this article, a machine learning algorithm was integrated into the solder paste inspection process to form an autonomous quality inspection system.

The data generated in the design and manufacture of tools and dies is rarely used in a targeted manner. However, it contains a significant wealth of knowledge that can be used to predict important parameters. For example, the metadata generated during the CAM programming of die-sinking electrodes can be used to extract parameters suitable to predict the subsequent erosion duration. A major hurdle in making data usable is their heterogeneity in number, format and employed terminology. This article presents a structured method for integrating heterogeneous data and making them queryable via a uniform interface. Its added value is demonstrated by means of a use case from die-sinking EDM.

The underlying article measures the search intensity of employers and job seekers as well as the placement intensity of employment agencies. For this purpose, we use daily data of online activities on the job exchange platform of the German Federal Employment Agency and its internal placement software. The investigation focuses on search and placement during the Corona crisis 2020. According to the results, the search and placement activities were severely reduced in the first lockdown. The following recovery was rather sluggish. The most critical effects of the Corona crisis on the labour market may be due to a lack of new hires.

With the advent of People Analytics Big Data are made operative on the level of personnel management. An algorithm-based screening and analysis of all kinds of employee-related data and behavioral traces is expected to guarantee evidence-based decisions in an organizational field once considered ‘soft’ and subjective. The article summarizes the objectives and challenges of such data-driven personnel management, as well as its implications for employees and corporate labour policies.

The Physical Internet is based on physical, digital, and operational interconnectivity, without which a globally fragmented and standardized freight transport system could not operate efficiently. Valid input data are necessary for the self-control of global flows of goods. In addition, a high level of trust in control decisions is essential for a far-reaching acceptance of all actors and customers in the logistics industry. These two goals can only be achieved by high data-quality. In addition to increasing data-quality through automation or the use of advanced sensor technology, methods of data-fusion and decision-fusion offer great potential. This article describes a methodical approach to analyze these potentials. Furthermore, this procedure is exemplarily carried out using a transit center.

Efficient product development can be a decisive factor in a company’s competition - it quickly falls behind who has to cope without simulation technologies. For large companies, these have long since become part of everyday life. But for small and medium-sized companies, they often remain wishful thinking for reasons of capacity and know-how. But: They, too, can benefit from the advantages of simulation with the right support and appropriate training programs.