Within their lifetime, products and processes pass through characteristic periods, which can be divided into distinct phases, such as design, production, use, and disposal. Specially, the production phase of products consumes a great amount of energy, non-renewable materials, renewable materials, ancillary inputs, and fossil fuels. Moreover, significant amounts of emissions (wastes, effluents, and greenhouse gases) are generated, which lead to sustainable impacts, such as extra costs, environmental damages, social issues. Through a systematic overview of resources and emissions during the production planning process, potential sustainable impacts can be identified and possibly avoided. The paper presents a concept for a fuzzy inference model to evaluate production programs for short- and mid-term production planning according to sustainable indicators. For this approach, the paper presents criteria to select applicable measurements for sustainable production planning, three categories of sustainable indicators to evaluate production programs, a procedure to develop the fuzzy inference model, and possible actions for optimizing production programs to increase the degree of sustainability. In future works, the fuzzy inference model will be implemented in enterprises to demonstrate the benefits of sustainable production planning.
|Number of pages||6|
|Publication status||Published - 1 Jan 2018|
|Event||10th CIRP Conference on Industrial Product-Service Systems, CIRP IPS2 2018 - Linkoping, Sweden|
Duration: 29 May 2018 → 31 May 2018
- Fuzzy Logic
- Production Planning
- Sustainable Manufacturing