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This paper presents an innovative methodology to help designers to pre-14 dict technological evolutions for more environmentally friendly products.

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In this paper, we propose a Fuzzy Cognitive Map (FCM) learning approach with a multi-local search in balanced memetic algorithms for forecasting industrial drying processes. The first contribution of this paper is to propose a FCM model by an Evolutionary Algorithm (EA), but the resulted FCM model is improved by a multi-local and balanced local search algorithm. Memetic algorithms can be tuned with different local search strategies (CMA-ES, SW, SSW and Simplex) and the balance of the effort between global and local search. To do this, we applied the proposed approach to the forecasting of moisture loss in industrial drying process. The thermal drying process is a relevant one used in many industrial processes such as food industry, biofuels production, detergents and dyes in powder production, pharmaceutical industry, reprography applications, textile industries, and others. This research also shows that exploration of the search space is more relevant than finding local optima in the FCM models tested.

An estimation of the water used for human consumption in hospitals is essential to determine possible savings and to fix criteria to improve the design of new water consumption models. The present work reports on cold water for human consumption (CWHC) in hospitals in Spain and determines the possible savings. In the period of 2005–2012, 80 Eco-Management and Audit Schemes (EMAS) from 20 hospitals were analysed. The results conclude that the average annual consumption of CWHC is 1.59 m3/m2 (with a standard deviation of 0.48 m3/m2), 195.85 m3/bed (standard deviation 70.07 m3/bed), or 53.69 m3/worker (standard deviation 16.64 m3/worker). The results demonstrate the possibility of saving 5,600,000 m3 of water per year. Assuming the cost of water as approximately 1.22 €/m3, annual savings are estimated as 6,832,000 €. Furthermore, 2,912 MWh of energy could be saved, and the emission of 22,400 annual tonnes of CO2 into the atmosphere could be avoided.