https://www.um.edu.mt/library/oar/handle/123456789/929 Wed, 26 Aug 2026 01:01:11 GMT 2026-08-26T01:01:11Z https://www.um.edu.mt/library/oar/handle/123456789/148589 Title: Towards an intelligent design support framework balancing risks and user experience : a case study in pharmaceutical packaging Authors: Bianco, Alessandra; Farrugia, Philip; Attard Pizzuto, Maresca Abstract: This paper presents a design support framework that focuses on linking product design with risk management within the pharmaceutical packaging industry. The framework is intended for use by packaging designers and adopts a multi-user perspective to identify design requirements and integrate them into risk mitigation activities. It promotes safe and effective packaging through proactive design, reducing costly redesign measures. A preliminary version is presented which has been developed through studies with key industry stakeholders, including pharmaceutical packaging designers. Thu, 01 Jan 2026 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/148589 2026-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/148588 Title: Structured prompting for design for multi-X : evaluating LLM support in early prosthetic device design Authors: Mercieca, Adrian; Farrugia, Philip; Borg, Jonathan Abstract: This paper investigates how prompt structure influences the use of Large Language Models in early engineering design. A structured prompting framework aligned with the engineering design cycle is proposed to support Design for Multi X reasoning and more coherent problem exploration. Using a prosthetic knee-cover case study, six engineering designers engaged with both generic and structured prompting workflows. A mixed methods study examines how prompt organisation shapes LLM assisted reasoning, problem framing and the articulation of design constraints and considerations. Thu, 01 Jan 2026 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/148588 2026-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/147124 Title: Physicochemical characterisation of difluprednate and 6α9α-difluoroprednisolone : determination of solubility, pKa and LogP Authors: Baluci, Giulia; Buhagiar, Paul Immanuel; Vella Szijj, Janis; Attard, Everaldo; Sammut Bartolo, Nicolette Abstract: Steroids are used in the treatment of diverse pathological conditions for their anti-inflammatory and immunosuppressive effects, with the mode of action being affected by their physicochemical characteristics. To date, difluprednate (DFBA) has been characterised using computational methods which rely on the selected computational model and disregard external factors. The aim of the study was to determine the solubility, pKa and LogP of DFBA and its metabolite, 6α9α-difluoroprednisolone (DFP) using experimental methods. Methods using UV–Visible spectroscopy and High-Performance Liquid Chromatography (HPLC) were developed to determine the solubility and the pKa, LogD and LogP of the selected steroids. The steroids are soluble in acetonitrile and methanol, and are insoluble in water. DFBA achieved a solubility of 5.76 mg/mL and 0.81 mg/mL in acetonitrile and methanol, while DFP achieved solubility of 2.29 mg/mL and 0.16 mg/mL, respectively. DFBA had an average LogP value of 3.2, and DFP had an average LogP of 1.5. The pKa values for DFBA were 1.5 and 7.2 and for DFP, were 5.9 and 10.8. The characterisation of the physicochemical properties of DFBA and DFP can help support efficient formulation development. Thu, 01 Jan 2026 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/147124 2026-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/147020 Title: Integrating environmental life cycle assessment in assistive technology selection for inclusive workstations : a novel multi-objective optimisation approach in industry 5.0 Authors: Bonello, Amberlynn; Refalo, Paul; Francalanza, Emmanuel; Gauci, Maria Victoria Abstract: Inclusive workstations embody human-centred design in manufacturing, the hallmark of Industry 5.0. Such workstations typically incorporate assistive technologies (ATs) that support understanding, training, assembly performance, and quality inspection for operators with various disabilities. That said, at present, ATs are normally only related to the social pillar of sustainability, with researchers typically overlooking the potential impacts of using ATs on environmental sustainability. This work contributes a novel approach that employs life cycle assessment (LCA) as a design-support tool to promote the cleaner engineering and sustainable selection of ATs without compromising on inclusivity on the manufacturing shopfloor. The outcomes of an LCA of nine different ATs, ranging from a collaborative robot to a projector, were integrated in a multi-objective optimisation (MOO) framework, to shortlist combinations of ATs that enhance physical, cognitive and sensory accessibility, whilst minimising adverse environmental impacts. From the resulting Pareto front, optimal (non-dominated) combinations of ATs were identified, providing up to 91% of the maximum normalised total accessibility. A 65% reduction in lifecycle environmental impacts was also achieved when compared to the maximum environmental impact, demonstrating the approach's capacity to inform cleaner engineering strategies in future assistive technology development. The proposed approach therefore serves as a design-feedback loop, enabling engineers to identify environmental ‘hotspots’ within AT devices and AT systems, and quantify how interventions at the design stage, may influence the Pareto-optimal combination in the age of Industry 5.0. Thu, 01 Jan 2026 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/147020 2026-01-01T00:00:00Z