The worker profiler
Assessing the digital skill gaps for enhancing energy efficiency in manufacturing
Bibliographic Data
| ID | 21401507 |
|---|---|
| Authors | Silvia Fareri (0000-0002-8849-9752, corresponding author), Riccardo Apreda, Valentina Mulas, Rubén Alonso (0000-0001-6062-9933, R2M Solution (Italy)) |
| Year | 2023 |
| Volume | 196 |
| Pages | 122844 |
| Publication date | 2023-11-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Technological Forecasting and Social Change (JOURNAL) |
| Journal identifiers | ISSN: 0040-1625 • E-ISSN: 1873-5509 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.techfore.2023.122844 |
| OpenAlex | W4386878923 |
| Language | EN |
| Citations received | 3 |
| References cited | 62 |
In recent years, the manufacturing sector has been responsible for nearly 55 % of total energy consumption, inducing a major impact on the global ecosystem. Although technological advances are increasing its sustainability, zero-emission and fuel-efficient manufacturing is still considered a utopian target. Moreover, a primary feature of Industry 4.0 is the digitization of production processes, which offers the opportunity to optimize energy consumption. However, given the speed and often unpredictability with which innovation manifests itself, tools capable of measuring the impact that technology is having professions are still being designed. In light of the above, in this article we present the Worker Profiler, a software designed to map the skills currently possessed by workers, identifying misalignment with those they should ideally possess to meet the renewed demands that digital innovation and environmental preservation impose. In more detail, the authors inferred the key technologies and skills for the topic, isolating those with markedly increasing patent trends and identifying green and digital enabling skills and occupations. Thus, the software was designed and implemented at the user-interface level. The output of the self-assessment is the definition of the missing digital and green skills that enable the definition of a customized retraining strategy
Business · Computer security · Consumption (sociology) · Digital manufacturing · Digitization · Efficient energy use · Energy consumption · Interface (matter) · Key (lock) · Manufacturing engineering · Retraining · Sustainability · Telecommunications · Computer Science · Digital Transformation in Industry · Energy Efficiency and Management · Engineering · Ergonomics and Human Factors · Software
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The Carbon Emission Characteristics and Reduction Potential in Developing Areas
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The Use of Patent Data for Technological Forecasting
| Citations per year | 1.5 |
|---|---|
| Citation span | 2024 - 2026 (3) |
| Highly cited | No |