In the realm of process engineering, the pursuit of sustainability is paramount. Traditional approaches can be time-consuming and often struggle to address modern environmental challenges effectively. This article explores the integration of generative AI, as a powerful tool to generate solution ideas and solve problems in process engineering using a Solution-Driven Approach (SDA). SDA applies nature-inspired principles to tackle intricate engineering challenges. In this study, generative AI is trained to understand and use the SDA patterns to suggest solutions to complex engineering challenges.

Three bentonite samples (B1, B2, B3) from Milos Island, Greece, were investigated by XRD, AAS, DTA-TG, FTIR and specific surface area measurement techniques. A laboratory batch study has been performed to investigate the adsorption characteristics of lead ions (Pb2+) onto natural bentonite samples. The effect of various physicochemical factors that influence adsorption, such as solution pH (2–6), adsorbent dosage (1–10 g L–1), contact time (20–360 min), and initial metal ion concentration (5–150 mg L–1) was studied. A number of available models like the Lagergren pseudo first-order kinetic model, the pseudo second-order kinetic model and intra-particle diffusion were utilized to evaluate the adsorption kinetics. The adsorption of Pb2+ was modelled with the Langmuir, Freundlich and D-R isotherms. The maximum Pb2+ adsorption capacities for B1, B2 and B3 were 85.47 mg g–1, 73.42 mg g–1 and 48.66 mg g–1, respectively.

This article describes the technical principles and representation of a constraint-based configuration method for work processes. Methods developed for the configuration of modular systems comprising components have traditionally adopted a representation where the properties and compatibility requirements are expressed as constraints associated with individual components. However, this representation does not accurately capture constraints on paths and subprocesses and is therefore unsuitable for process configuration. This article extends established constraint-based configuration methods with a constraint language for specifying properties of execution paths in work processes. A framework for semiautomated process customization is presented. It integrates the extended constraint language with a metamodel of the work processes in an organization and allows to adapt generic work processes to fit the requirements of specific development projects. Heuristic search methods are applied to build valid process configurations by incrementally resolving constraint violations. The declarative framework facilitates the adaptation of abstract work processes as well as the validation and repair of existing processes. The approach was developed in the context of a real-world system of complex design and development processes where it was shown that significant process improvements and reduction in effort required to edit process models can be achieved.