Decision Making for Sustainable Technical Applications with the SMH Approach
| Autor: | Philipp Kranabitl, Hannes Hick, Clemens Faustmann |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Computer science
020209 energy Geography Planning and Development TJ807-830 02 engineering and technology 010501 environmental sciences Management Monitoring Policy and Law TD194-195 01 natural sciences Renewable energy sources decision making Order (exchange) model-based systems engineering 0202 electrical engineering electronic engineering information engineering GE1-350 Systems thinking Acronym Chief executive officer 0105 earth and related environmental sciences Sustainable solutions model cube Environmental effects of industries and plants Renewable Energy Sustainability and the Environment Model-based systems engineering systems thinking sustainability SMH approach credition Environmental sciences Identification (information) Risk analysis (engineering) Sustainability human factor ecosystem model cube |
| Zdroj: | Sustainability Volume 13 Issue 16 Sustainability, Vol 13, Iss 8702, p 8702 (2021) |
| ISSN: | 2071-1050 |
| DOI: | 10.3390/su13168702 |
| Popis: | Decision-making is becoming more and more challenging due to the rise in complexity of modern technical products. A lot of industries are currently at a crossroads, and a wrong strategic or technical decision may have disastrous consequences for the future of the company. Within this paper, the SMH approach, that supports decision making processes to put emphasis on sustainable solutions regarding strategic and technical aspects, is introduced. SMH is an acronym that stands for a decision making approach that includes systems thinking (S), model-based systems engineering (M) and the human factor (H). This approach deals with the challenge to consider overall boundary conditions and interactions of the system, the decision which models need to be built in order to have the best data support possible, and the identification what influence the human factor plays in analyzing the data and the consequent decision making based on it. The importance of the human factor is often neglected in technical processes, which may lead to costly mistakes. This theoretical approach is applied to the use case of a chief executive officer (CEO) who has to decide on allocation of research and development (R& D) resources to future powertrain technologies. |
| Databáze: | OpenAIRE |
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