Environmental Sustainability Drivers: A Study on Malaysian Palm Oil Industry

Industrial practitioners and policy makers in the Malaysian palm oil industry are now focusing on understanding the factors that influence sustainability of palm oil supply chain network involving the fundamental principle of triple bottom line of social, environmental, and economic performance impacts of supply chain network design. In order to achieve sustainable products, an interpretive structural modelling approach method was used to better understand the drivers related to environmental sustainability reporting in the supply chain network related to the Malaysian palm oil industry. This paper has identified nine (9) environmental sustainability drivers (environmental management, life cycle assessment, green labelling, GHG emissions, climate change, energy efficiency, renewable resources, water, soil and air quality and lastly waste management) and the relationships between them. The findings from the environmental sustainability reporting drivers of this study can be furthered use to explore the potential impacts of supply chain network design on sustainability using the Malaysian palm oil industry as a reference. The novelty of this research is that it identifies the significance of environmental sustainability reporting based on the analyzed drivers and provides evaluation of environmental sustainability criteria’s. This paper has provided a structural model of environmental sustainability and its associated method was developed by using the interpretive structural modeling model to determine the potential drivers in environmental sustainability reporting

Simulating bio-composite cycling helmet performance through FEA and CFD approaches

Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD) analysis were performed in this work in order to obtain the best design for safety and aerodynamic performance of the bicycle cycling helmet. FEA analysis was computed on two different helmet designs to determine the critical area subjected to impact. A pressure load was applied on the helmets’ outer surface to simulate oblique loading. The critical areas of the helmets were then highlighted and identified, enabling design improvements to be made on both designs. CFD analysis was then executed in order to obtain the lowest drag coefficient number in reducing the air resistance induced by both of the helmet designs, inherently increasing cyclist performance and ensuring competition success

Smart energy meter based on a long-range wide-area network for a stand-alone photovoltaic system

Long-range wide-area network (LoRaWAN) has emerged as a key technology for Internet of Things (IoT) applications worldwide owing to its cost-effectiveness, robustness to interference, low power, licensed-free frequency band, and long-range connectivity, thanks to the adaptive data rate. In this contribution, an IoT-enabled smart energy meter based on LoRaWAN technology (SEM-LoRaWAN) is developed to measure the energy consumption for a photovoltaic (PV) system and send real-time data to the utility/consumers over the Internet for billing/monitoring purposes. The proposed SEM-LoRaWAN is implemented in a PV system to monitor related parameters (i.e., voltage, current, power, energy, light intensity, temperature, and humidity) and update this information to the cloud. A LoRa shield is attached to an Arduino microcontroller with several sensors to gather the required information and send it to a LoRaWAN gateway. We also propose an algorithm to compose data from multiple sensors as payloads and upload these data using the gateway to The Things Network (TTN). The AllThingsTalkMaker IoT server is integrated into the TTN to be accessed using Web/mobile application interfaces. System-level tests are conducted using a fabricated testbed and connected to a solar panel to prove the SEM-LoRaWAN effectiveness in terms of functionality, simplicity, reliability, and cost. The connectivity between the system and users is achieved using smartphones/laptops. Results demonstrate a smooth system operation with detailed and accurate measurements of electrical usage and PV environmental conditions in real-time

Crashworthiness Behaviour on Aluminum Foam Bumper Beam and Side Member System under Oblique Impact

Abstract This paper presents the simulation of crush behavior for side members and bumper beam under axial and angular impact loading. Recent issues of automotive industry are to reduce weight and to improve occupant safety. Aluminum foam as a lightweight material was selected due to its excellent energy absortion capacity. Various parameters have been considered, such as angles of load, geometry and the material selection, aluminum alloy (AA6063 and AA6060) . Bumper beam connected two side members were impacted load angles of 0˚ to 30˚ from longitudinal axis. The finite element analysis approach using the specific software package has determined the crashworthiness parameters, that were specific energy absorption (SEA) and crush force efficiency (CFE). The outcome of this study have formulated functions for calculating of crush parameters