Jose Swaminathan

In bottling process plants, safety conformity effectively addresses hazard control, workers well being and product integrity, promising the protection of the bottling plants from risks and building trust in them. Currently, insufficient attention from comparing safety managers hinders safety conformity development. To address this, the present study aims to explore how the combination of NGT (nominal group technique), DEMATEL (Decision Making Trial and Evaluation Laboratory) and PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation) is used to concurrently evaluate the interrelationship and prioritize parameters according to their importance. The study analyzed five relevant segmental classifications of the plant, identified 29 parameters affecting the promotion of safety conformity and constructed an outranking flow model based on aggregate preference function on the leaving-entering flow matrix. The alternate comparison scheme was used to identify the key parameters associated with each of the five segments, namely, warehouse, manufacturing corridors, quality assurance, fleet of vehicles and contractors. Subsequently, the highest-to-lowest ranking of parameters according to the respective aforementioned segments are forklift drivers (aggregate 7; P, P-1, R, I → 7,0,0,0), sighters (aggregate 6; P, P-1, R, I → 6,0,0,0), syrup mixers (aggregate 5; P, P-1, R, I → 5,0,0,0), welders (aggregate 2; P, P-1, R, I → 2,0,0,0) and security (aggregate 4; P, P-1, R, I → 4,0,0,0) in segments 1 to 5, respectively. The study reveals the safety conformity influential parameters with which the most of effective changes and complaints with regulations could be attained. The study results provided guidance and understanding to locate the most influential parameters with high interactions with others, and a platform to drastically enhance safety conformity.

A numerical and experimental study was conducted on an evacuated tube compound parabolic concentrator (ET‐CPC) with a thermosyphon heat pipe (THP). The heat transfer behaviour was analysed using regional solar irradiation data, and the results were compared with steady‐state and transient flow simulation performance analysis and experimental data. The thermal performance of water glycol as a working fluid in a THP under varying solar inputs was evaluated. Steady‐state analysis assumes uniform solar insolation and radiative heat transfer across the vacuum gap, whereas the thermosyphon is represented by a high effective conductivity and condenser heat sink. Experimental testing was conducted on 21 ^st June, recording the temperature profile, heat gain and heat loss throughout the day. The water–glycol mixture reached a peak temperature of 144°C, and the aluminium enclosure with insulation reached 41.65°C. Experimental maximum solar irradiance was 893.5 W/m ² , with an evaporator maximum of 202.04°C. The heat pipe gained a total of 1799 kWh of heat energy over the day, whereas the total heat loss was 1.699 kWh. The temperature profile and heat gain analysis showed strong agreement across all methods. The validation confirmed that the numerical model closely matched the measured performance, demonstrating its reliability in predicting the thermal behaviour of ET‐CPC solar collectors with THP.

E-commerce is transforming agriculture by overcoming logistical issues and improving sustainability. This research analyzes the approaches and technologies in practice and provides recommendations for the experimental farm at Universidad Francisco de Paula Santander. The major results underline five essential components that the customer primarily considers-purchase behavior, experience, service, even a history of use, and product quality-and the impact of predictive analytics and blockchain in establishing trust and optimizing processes. E-branding strategies promote further development of product positioning focusing on quality and sustainability. An inclusive e-commerce platform is suggested to enhance market penetration, and productivity, and create the university farm as a center of the best practices in innovation and sustainability.

This project explored the manufacturability-driven design of mandibular reconstruction implant models made using extrusion-based additive manufacturing. A formalized multi-objective optimization framework was presented for the identification, collection, and mapping of the manufacturability constraints in the design model. This workflow ensures the manufacturability of the final product while also optimizing factors related to geometry, fit, structural integrity, material usage, and biocompatibility. This framework captured the realistic requirements driven by manufacturing processes to ensure that the final design could be manufactured. The method was demonstrated using a detailed case study that included the manufacturing and analysis of the final components and validation of the design, which clearly showed both the opportunities and limitations of engineering plastics for models. The case study results showed design success related to manufacturing, fit, material utility, and biocompatibility, but it was clear that the plastic models were not able to be used directly due to structural concerns. However, they proved to be excellent form/fit prototypes or casting forms for metal or ceramic implants. Common commercial software tools (Materialise Mimics, Autodesk Meshmixer, and nTop) were used throughout the process, making the method more accessible to practical users. This validated methodology will be useful both in the computer-aided design (CAD) and in medical device domains, as it allows the direct application of design-for-additive manufacturing principles during the design of custom implants. Unlike previous works, this design framework integrates manufacturability and performance constraints simultaneously. Graphical