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The correlations between mechanical behaviour, tensile strength, and rock parameters of metasedimentary rock samples in Karak, Pahang’s New Austrian Tunnelling Method (NATM) were statistically evaluated from the rock mechanic laboratory works at the selected sections around 2,000 m of the tunnel (named as NATM-1). According to a statistical analysis, lithotypes, geological structures, and region geology have a significant impact on the mechanical behaviour of the metasedimentary rock. In the Brazilian test, the fracture behaviour of the disc specimens was highly related to the reliability and precision of the experimental data by validations of methods. In this work, the impact of different loading methods and rock lithotypes on the failure mechanism of Brazilian discs was examined utilising five different metasedimentary rock types and three different loading methods. During the loading operation, the strain and displacement fields of the specimens were recorded and evaluated using a computerised strain gauge system. The rock types, according to experimental data, have a significant impact on the peak load and deformation properties of Brazilian discs. With the method below, tensile strength point of a disc specimen is clearly regulated by the material stiffness and tensile–compression ratio. Seismic occurrences have had a substantial impact on changing the rock and exerting forces that may affect its mechanical characteristics as well as its vulnerability to weathering effects or discontinuities. As a result, the goal of this study is to look into the connection between rock mechanics and metasedimentary rock stress analysis in NATM-1, Karak, Pahang.

Purpose – This purpose of the research is to investigate the process of manufacturing LDPE recycle thermoplastic composites with reinforcement oil palm empty fruit bunch (OPEFB) biomass microfillers.

Design/Methodology/Approach – Methods of physical and chemical modification of OPEFB fibers into the LDPE matrix and the addition of some compatibilizer such as MAPE and xylene process through melt blending can improve mechanical properties, electrical properties, biodegradability, and improve the morphology of composites.

Research Limitations/Implications – These composites are prepared by the following matrix ratio: filler (70:30)% and filler size (63, 75, 90, and 106) μm. The LDPE plastic is crushed to a size of 0.5–1 cm, then pressed with hot press free heating for 5 min and with a pressure of 10 min at 145 °C. Based on the characterization obtained, the tensile strength and the high impact on the use of 106 μm filler is 13.86 MPa and 3,542.6 J/m², and thermal stability indicates the degradation temperature (T₀) 497.83 °C. FT-IR analysis shows the presence of functional groups of cellulose and lignin molecules derived from TKKS collected in the composite.

Practical Implications – Based on the characterization obtained, this composite can be applied as furniture material and vehicle dashboard.

Originality/Value – Composites obtained from recycle of LDPPE plastics waste has some advantages such as good compatibility and high tensile strength. This composite used the OPEFB filler whose size is in micrometer, and so this product is different from other products.

Composites based on fiber are commonly used in high-performance building materials. The composites mostly use petrochemically derived fibers like polyester and e-glass, due to their advantageous material features like high stiffness and strength. All the same, these fibers also have important shortcomings related to energy consumption, recyclability, initial processing expense, resulting health hazards, and sustainability. Increasing environmental awareness and new sustainable building technologies are driving the research, development, and usage of “green” building materials, especially the development of biomaterials.

In this chapter, the natural fiber evaluation approach is applied, which covers a diverse set of criteria. Consequently, the comparative assessment of diverse natural fiber types is applied through the use of an expert decision system approach. The best performing fiber choice is made by comparatively evaluating the materials related to green building. The proposed fiber can be used and applied by green building material manufacturing companies in various countries or locations as a reference when selecting the fiber with the best performance.

The increasing accumulation of synthetic plastic waste in oceans and landfills, along with the depletion of non-renewable fossil-based resources, has sparked environmental concerns and prompted the search for environmentally friendly alternatives. Biodegradable plastics derived from lignocellulosic materials are emerging as substitutes for synthetic plastics, offering significant potential to reduce landfill stress and minimise environmental impacts. This study highlights a sustainable and cost-effective solution by utilising agricultural residues and invasive plant materials as carbon substrates for the production of biopolymers, particularly polyhydroxybutyrate (PHB), through microbiological processes. Locally sourced residual materials were preferred to reduce transportation costs and ensure accessibility. The selection of suitable residue streams was based on various criteria, including strength properties, cellulose content, low ash and lignin content, affordability, non-toxicity, biocompatibility, shelf-life, mechanical and physical properties, short maturation period, antibacterial properties and compatibility with global food security. Life cycle assessments confirm that PHB dramatically lowers CO₂ emissions compared to traditional plastics, while the growing use of lignocellulosic biomass in biopolymeric applications offers renewable and readily available resources. Governments worldwide are increasingly inclined to develop comprehensive bioeconomy policies and specialised bioplastics initiatives, driven by customer acceptability and the rising demand for environmentally friendly solutions. The implications of climate change, price volatility in fossil materials, and the imperative to reduce dependence on fossil resources further contribute to the desirability of biopolymers. The study involves fermentation, turbidity measurements, extraction and purification of PHB, and the manufacturing and testing of composite biopolymers using various physical, mechanical and chemical tests.

The consideration of alternative sources of material for construction is imperative to reduce the environmental impacts as two-fifths of the carbon footprint of materials is attributed to the construction industry. One alternative material with improved biodegradable attributes which can contribute to carbon offset is bamboo. The commercialisation of bamboo in modern infrastructures has significant potential to address few of the Sustainable Development Goals (SDGs) itemised by the United Nations, namely SDG 9 about industry, innovation and infrastructure. Other SDGs covering sustainable cities and communities, responsible consumption and production and climate action are also indirectly addressed when utilising sustainable construction materials. Being a natural material however, the full commercialisation of materials such as bamboo is constrained by a lack of durability. Besides fracture mechanisms arising from load-induced cracks and thermal modification, the durability of bamboo material is greatly impaired by biotic and abiotic factors, which equally affect its natural rate of degradation, hence fracture behaviour. In first instance, this chapter outlines the various factors leading to the durability limitations in bamboo material due to load-induced cracks and natural degradation based on recent findings in this field from the author's own work and from past literature. Secondly, part of this chapter is devoted to a new approach of processing the surge of information about the varied aspects of bamboo durability by considering the powerful technique of artificial intelligence (AI), specifically the artificial neural network (ANN) for prediction modelling. Further use of AI-enabled technologies could have an impactful outcome on the life cycle assessment of bamboo-based structures to address the growing challenges outlined by the United Nations.

The role of management control has not received sufficient attention in the literature on value creation so far. Therefore, this paper aims to investigate the role of control in value creation in industrial networks. More specifically, the aim is to examine the management and control of interfaces between key resources within and between firms, in the networks surrounding firms, when they attempt to create value. All the firms that take part in a value-creation process have both formal and informal control systems: these firms have budgets, specific routines, reward systems, and sanctioned “ways to behave.” The paper relates the Industrial Marketing and Purchasing (IMP) group's research on interaction, relationships, and networks with control literature, and presents a framework for controlling resource interfaces in a network setting. Two in-depth cases illustrate the role of control in value creation. The first case covers the development of a low-weight newspaper grade that Holmen and its paper mill Hallsta initiated. The second case examines the attempt to develop and commercialize a new, energy efficient pulping technology.

This chapter offers an overview of the applications of artificial intelligence (AI) in the textile industry and in particular, the textile colouration and finishing industry. The advent of new technologies such as AI and the Internet of Things (IoT) has changed many businesses and one area AI is seeing growth in is the textile industry. It is estimated that the AI software market shall reach a new high of over US$60 billion by 2022, and the largest increase is projected to be in the area of machine learning (ML). This is the area of AI where machines process and analyse vast amount of data they collect to perform tasks and processes. In the textile manufacturing industry, AI is applied to various areas such as colour matching, colour recipe formulation, pattern recognition, garment manufacture, process optimisation, quality control and supply chain management for enhanced productivity, product quality and competitiveness, reduced environmental impact and overall improved customer experience. The importance and success of AI is set to grow as ML algorithms become more sophisticated and smarter, and computing power increases.