Manufacturing Engineering

Frequent repair and reconstruction activities required on existing pavements lead to significant expenses for highway agencies and road users. Economic loss and inconveniences resulting from frequent road maintenance and rehabilitation activities led researchers and practitioners to seek pavement alternatives that have longer service lives and, at the same time, have lower life-cycle costs. One such alternative developed by the asphalt industry was the design and construction of perpetual pavements. Several studies have compared conventional pavements to perpetual pavements, focusing primarily on construction, maintenance, and rehabilitation-related financial costs. With environmental sustainability gaining importance as a component of decision-making processes, it is critical to compare the environmental impacts of these pavement alternatives. This paper uses life cycle assessment (LCA) to accomplish this objective. This paper also focuses on studying the benefits that will ensue from the combination of reduced-temperature warm mix asphalt (WMA) and perpetual pavement concepts. Therefore, alternatives considered in this study include: (1) a hot mix asphalt (HMA) conventional pavement, (2) an HMA perpetual pavement, and (3) a WMA perpetual pavement. AASHTO 1993, PerROAD, and TxME were used to design the pavement structures. The LCA was carried out over a 50-year analysis period, and it involved all cradle-to-grave life cycle stages of a pavement, excluding the use phase. The maintenance and rehabilitation of the pavements were scheduled based on performance prediction results. Opting for a hot-perpetual pavement instead of a hot-conventional pavement resulted in lower environmental impacts in all five impact categories considered. Moreover, when the perpetual pavement was constructed using WMA instead of HMA, further improvements in three out of the five impact categories were realized.

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Climbing robots that integrate an articulated arm as their main climbing mechanism can eventually take advantage of their arm for plane transition and thus to operate on 3D structures rather than only climbing planar surfaces. However, they are usually slower than wheel based climbing robots. Within this research we address this problem by integration of a light-weight arm and adhesion mechanism into an omnidirectional wheel based climbing robot, thus forming a hybrid mechanism that is agile in climbing and still able to perform plane transition. A 2DOF (Degree of Freedom) plannar mechanism with 2 linear actuators was designed as a light-weight manipulator for the transition mechanism. Furthermore, we customized and developed actuated switchable magnets both for the robot chassis and also as the adhesion unit of the arm. These units allow us to control the amount of magnetic adhesion force, resulting in better adaptation to different surface characteristics. The adhesion units are safe for climbing applications with a very small power consumption. The conceptual and the detailed design of the mechanisms are presented. The robots were developed and successfully tested on a ferromagnetic structure.

Integrating Machine Learning (ML) with optimization algorithms in 3D printing, also known as Additive Manufacturing (AM), has revolutionized the creation and production of complex structures. This integration has significantly boosted material efficiency, print quality, and optimization of the entire process. This paper delves into details on improving 3D printing design and production workflows using advanced ML techniques such as neural networks, Reinforcement Learning (RL), and optimization techniques, such as topology optimization and genetic algorithms. The proposed framework offers a 15-25% reduction in print time and material consumption and a 10-20% improvement in predictive accuracy over existing methods. Additionally, the results of the multiobjective optimization reveal an aligned improvement in cost-effectiveness, structural strength, and mechanical performance. Stress-strain analysis showed that optimized designs can achieve up to a 12% increase in yield strength, while defect rates decrease by up to 30% by applying dynamic RL for parameter adjustments. The results validate the effectiveness of these hybrid models, emphasizing their potential to boost reliability, efficiency, and scalability in additive manufacturing processes.

Over the past decade, significant progress has been made in the identification of novel material binding peptides having affinity to a wide range of target materials and their use in nanobiotechnological innovations. These material binding peptides (MBPs), also known as solid/ substance binding peptides (SBPs) can be isolated using combinatorial display technologies such as phage display (PD), surface display (cell, bacterial, yeast, mRNA) exhibit material specific selectivity and affinity towards a range of inorganic and organic nanomaterial surfaces including metals, metal oxides, minerals, semiconductors and biomolecules. MBPs serve as mediators in bringing nanotechnology and biotechnology under one umbrella by linking solid nanoparticles with biomolecules including proteins, bioactive peptide motifs, bifunctional binding peptides, enzymes, antigens and antibody fragments. As the utilization and application of these inorganic binding peptides as molecular connectors, molecular assemblers and material specific synthesizers in nanotechnology has been expanding rapidly, so too has growing commercial interest in patenting such innovations. In this review, we present the past, current and future developments and applications of inorganic MBPs specific to nanomaterials and their applications.

This study explores a large language model (LLM)-based system enhancing design methodology education, focusing on design for environment (DfE). By integrating GPT-4 with DfE guidelines and a dual-loop structured learning workflow, we developed an interactive system addressing persistent challenges in design method learning. Through personalised exercises and systematic feedback, our system guided beginners in applying DfE strategies while fostering self-directed learning. Experiments involving 30 participants revealed significant improvements across Bloom's taxonomy domains, particularly when learners demonstrated sustained or developing proactiveness. This study analysed how LLM-based systems can support education for various design for X methodologies through generalizable interaction frameworks.

In many institutions, classroom furniture does not meet any national ergonomic criteria. This study aimed to use the concept of ergonomics to design a classroom desktop-chair for students in Uasin-Gishu County, Kenya. Anthropometric data were collected from a total of 382 students of both genders. The fourteen anthropometric measurements were taken from students with the help of anthropometric tools. The research applied fundamental engineering principles of product design and was carried out in compliance with ISO 7250-1:2017. The data obtained was analysed using Minitab 17.0 statistical package. Using the collected anthropometric data, a students' desktop-chair was proposed. In conclusion, one type of ergonomically suitable classroom desktop-chair design was proposed to improve the match between classroom desktop-chairs' dimensions and students' anthropometric characteristics. It is highly recommended that similar scientific research should be carried out in other countries.

Nanostructured materials have attracted much research over the recent years, as they provide the critical building blocks for the booming of nanoscience and nanotechnology. Nanostructures have novel properties due to the interplay between the size confinement of electrons in small structures and proximity effects. This is relevant for example in device miniaturization towards the Tbit/in recording density and in the thermal stability of the recorded bits. Nanofabrication by self-organized templates, in particular nanoporous alumina membranes, is being explored intensively due to the fact that it might enable mass production over large areas.

Among the actions proposed by the European Union for the implementation of Circular Economy is the use of waste as a secondary raw material (SRM). During the fusion of the scrap, a steel dust is generated, named Electric Arc Furnace Dust (EAFD). The EAFD is composed mainly of potentially leachable heavy metals, so is classified as "hazardous" waste. Around the world, approximately 70% of this waste is deposited in landfills, with a previous treatment through cement-based materials to prevent the metals' mobility. However, this action is not in accordance with the Circular Economy concept due to the greater use of resources and the loss of deposited metals. The present investigation analyses the use of EAFD as SRM in conventional mortar production for its use as a construction material. Different substitution percentages (25%, 50% and 100%) were used replacing siliceous filler by EAFD. The investigation analysed the behaviour of conventional mortars by tests of workability, compressive strength, water absorption by capillarity and leaching behaviour in granular and monolithic state. The results obtained indicate a slight improvement in mechanical behaviour with the incorporation of EAFD, the reason why its use as SRM in conventional mortars would benefit the construction industry and would encourage the Circular Economy. From an environmental point of view, the mechanisms of Pb fixation should be improved in granular state.

In the pursuit of enhancing manufacturing competitiveness in India, companies are exploring innovative strategies to streamline operations and ensure product quality. Embracing Lean principles has become a focal point for many, aiming to optimize profitability while minimizing waste. As part of this endeavour, researchers have introduced various methodologies grounded in Lean principles to track and mitigate operational inefficiencies. This paper introduces a novel approach leveraging deep learning (DL) techniques to detect early failures in manufacturing systems. Initially, real time data is collected and subjected to a normalization process, employing the weighted adaptive min-max normalization (WAdapt-MMN) technique to enhance data relevance and facilitate the training process. Subsequently, the paper proposes the utilization of a triple streamed attentive recalling recurrent neural network (TSAtt-RRNN) model to effectively identify Lean based manufacturing failures. Through empirical evaluation, the proposed approach achieves promising results, with an accuracy of 99.23%, precision of 98.79%, recall of 98.92%, and F-measure of 99.2% in detecting early failures. This research underscores the potential of integrating DL methodologies with customer relationship management (CRM) data to bolster early failure detection capabilities in manufacturing, thereby fostering operational efficiency and competitive advantage.

Nowadays, advanced manufacturing models such as the Stream-of-Variation (SoV) model have been successfully applied to derive the complex relationships between fixturing, manufacturing and datum errors throughout a multi-stage machining process. However, the current development of the SoV model is still based on 3-2-1 fixturing schemes and, although some improvements have been done, e.g. N-2-1 fixtures, the effect of general workholding systems such as bench vices or 3-jaw chucks has not yet been included into the model. This paper presents the extension of the SoV model to include fixture and datum errors considering both bench vices and 3-jaw chucks as a fixturing devices in multi-stage machining processes. The model includes different workholding configurations and it is shown how to include the workholding accuracy to estimate part quality. The extended SoV model is validated in a 3-stage machining process by both machining experimentation and CAD simulations.

This paper proposes a postprocessor which applies the appropriate rotation rules to reduce the kinematic error (KE). Our first contribution is an algorithm which minimizes the KE using the Hausdorff distance. The shortest path algorithm includes the constraints relevant to the limits of the linear and the rotation axis. The proposed procedure is compared with state-of-the-art methods. It demonstrates an advantage in terms of the kinematic error for test surfaces characterized by a sharp curvature. The second contribution is testing interpolation methods of the STL surfaces. The first step of this procedure is the evaluation of the tessellation error (TE), i.e., the difference between the actual surface and the local or global interpolation obtained from the STL file. The numerical results show that a simple local interpolation using normal vectors proposed by Nagata performs well. The method has been tested against several state-of-the-art interpolation procedures, demonstrating a significant advantage. The proposed elements are integrated into a postprocessor. The experiments have been performed on a virtual and the actual tilt-table five-axis machining center (Haas VF-2TR).

The concept of zero waste manufacturing has surfaced as a revolutionary method for attaining sustainability, transitioning from the conventional linear economy to a circular economy (CE). This comprehensive review delves into the conceptual underpinnings, motivating factors, obstacles, illustrative case studies, technological advancements, regulatory structures, and evaluation metrics linked to zero waste manufacturing. The tenets of circular economyminimizing resource consumption, repurposing materials, reclaiming waste, and innovating product designs-provide both ecological and financial advantages, such as diminished resource exhaustion, decreased carbon footprints, and enhanced cost efficiency. Although it holds great promise, the implementation of zero waste manufacturing encounters considerable obstacles, such as technological constraints, elevated expenses, absence of uniform recycling methods, and reluctance to embrace change. Significant advancements like chemical recycling, resource tracking through IoT, 3D printing technology, and modular design are improving sustainability; however, they demand considerable financial commitment. Moreover, regulatory structures such as the EU Circular Economy Action Plan and China's Circular Economy Promotion Law are instrumental in advancing zero waste initiatives, although the implementation of these measures often lacks consistency. Case studies across diverse sectors such as construction, fashion, and electronics showcase effective implementations while also uncovering unique challenges specific to each industry. Successful collaboration among stakeholders-including governmental bodies, enterprises, and consumers-is essential for amplifying zero waste initiatives. Additionally, indicators like material recovery percentages, reductions in carbon footprints, and rates of waste diversion play a crucial role in assessing advancement. Subsequent investigations ought to concentrate on evaluating long-term effects, the behavioural elements that affect adoption, and the contribution of AI in enhancing resource utilisation. This evaluation highlights the critical need to shift towards zero waste production to guarantee ecological sustainability, economic robustness, and worldwide resource stability.

Grinding with power tools includes precision applications, such as polishing and engraving, but also high-performance applications such as cutoff grinding and deburring in foundries or construction. There is a growing demand for power tools in both industrial and consumer markets, but there is little literature on the sustainability of grinding with power tool available. Therefore, this paper summarizes the input-outputstreams of manual grinding and reviews sustainability aspects, in particular the energy source of abrasive power tools, layout of grinding tools, safety, and health. A survey on angle grinders showed how companies advertise in particular social and economic features, but not environmental features. The discussion demonstrates that much work needs to be done on the sustainability of grinding with power tools.

A general variational formulation for the determination of natural frequencies and mode shapes of free vibration of symmetric laminated plates of trapezoidal and triangular shapes is presented in this work. The kinematics corresponding to the first order shear deformation plate theory (FSDT) is used to take into account the effects of shear deformation and rotatonial inertia in the analysis. The developed approach is based on the Ritz method and the plate geometry is approximated by non-orthogonal right triangular co-ordinates. The transverse deflection and two rotations of the laminate are independently approximated by sets of simple polynomials. The algorithm allows obtaining approximate analytical solutions for laminated plates with different shapes, aspect ratio, number of layers, stacking sequence, angle of fiber orientation and boundary conditions including translational and rotational elastically restrained edges. The algorithm is simple to program and numerically stable.

This paper deals with the free transverse vibration of anisotropic plates with several arbitrarily located internal line hinges and piecewise smooth boundaries, elastically restrained against rotation and translation. The equations of motion and the associated boundary and transition conditions are derived using Hamilton's principle in a rigorous framework. A new analytical manipulation based on a condensed notation is used to compact the corresponding analytical expressions. A combination of the Ritz method and the Lagrange multipliers method with polynomials as coordinate functions is used to obtain tables of the nondimensional frequencies and the corresponding mode shapes, for rectangular plates with different boundary conditions and restraint conditions in the internal line hinges. The cases not previously treated of two-and three line hinges are particularly analyzed.

In this work the authors investigate how target sputtering, dose retention, and damage formation is generated in thin-body semiconductors by means of energetic ion impacts. The problems associated with ion implanting or plasma doping Si thin-bodies are well documented, however it is not clear how changing the target material to other semiconductors currently being considering for multi-gate field-effect transistor devices will counteract or enhance these effects. By means of Binary Collision Approximation based modeling with The Stopping and Range of Matter (SRIM) software, we explore the consequences of different target atomic density, lattice density, surface binding energies, and lattice binding energies on target sputtering, dose retention, and damage formation.

Today's aerospace assembly is a huge manual task according to strictly controlled instructions, where different operators are responsible for different areas. This harmonizes with the overall lean approach, but the assembly is very time-consuming and some tasks are not ergonomically friendly, such as assembly tasks inside a wing box. Here, it could be possible to increase automation with the aim to facilitate a shorter assembly time and ergonomically improved workplace. This paper will present different assembly cell concepts utilizing different safety strategies to achieve human-robot cooperation in an aerospace industry assembly line. These concepts will be discussed in relation to a case in the aerospace industry. The paper concludes with suggestions for three conceptual human-robot cooperation layouts. These are based on previous research in the areas of safety and human-robot cooperation, in combination with observations from an aerospace assembly line.

Robot rehabilitation is an introduction to rehabilitation robotics, and it’s suitable for anyone who needs help. This proposed technology exists in robots and has applications in various pathologies for scientists and doctors. In this research, we designed a knee joint exoskeletal and ankle with a new model, such as mechanical structure and damper hydraulic. It is essential to define knee joint and ankle exoskeletal spring parameters such as torque, movement, angle movement, movement speed, and degree of freedom. At first, kinematic analysis with rehabilitation robots based on Lagrangian polynomials should be done. Second, knee joints and ankle exoskeletal joints should be adjusted, and simulation will be done on the ADAMS and MATLAB platforms. Then, knee joint and ankle exoskeletal spring parameters are selected based on simulation results, such as spring power, spring stiffness, and spring expansion in the main parameters. At last, the states for this rehabilitation robot include those obtained from ADAMS and MATLAB simulation, clinical gait analysis states, and Lagrangian polynomials calculated states. The obtained results of the simulation represent that those results are well matched. Effectiveness simulation in ADAMS and MATLAB analysis proves that damper hydraulic parameters can meet the real needs of rehabilitation robots. Based on the proposed method, a simulation model of knee joint and ankle exoskeletal mobility is proposed. In recent research, there has been no matching literature or method in this form.

This pilot study develops a process to evaluate in-situ defect detection and self-healing in Ti-6Al-4V fabricated using laser-based powder bed fusion. A tailor-made test specimen was designed and manufactured for the nanofocus tube X-ray computed tomography (XCT) system. In situ optical tomography was used to capture infrared images containing heat signatures of the hot laser interaction zone. Depicting natural process variation, defective regions were seeded using process manipulation (up to ±30%) in proximity of the experimental standard volumetric energy density (VED). The concomitant defects and heat signatures were both spatially and temporally captured. The results indicate that porosity significantly grows from an average value of 27 parts per million (PPM) to a value of 337 PPM comprising defect sizes of <112 µm when the VED increases by 30%. The outcome confirmed that Ti-6Al-4V can self-heal these defective regions by up to 7 ± 1 layers using the standard VED. A convolutional neural network was trained (n = 211) and was verified with XCT. The model demonstrated prediction accuracy of 94% for the six classes of unfamiliar defective regions. This work enables in-situ detection and healing of defective regions caused by process uncertainty that can shift the quality frontier of novel product design and development.

Akee apple leaves extract (AALE) was tested for inhibition of corrosion of mild steel in sulphuric acid solution using gravimetric and gasometric measurement. The corrosion of mild steel was investigated at 40-60 0 C in 2M H2SO4 solution. The result of the inhibition revealed AALE efficiently delayed the dissolution of mild steel with inhibition efficiency obtained from gravimetric and gasometric at 60 0 C are 72.19 % and 74.32 % at addition of 0.5 g/l concentration of AALE respectively. The increase in inhibitor (AALE) concentrations results in decrease in corrosion rate and increase in inhibition efficiency. The inhibitive adsorption parameters show the corrosion process followed the Langmuir adsorption isotherm with physical adsorption mechanism. Finally, the kinetic parameters established the corrosion process was endothermic reaction and occurred with spontaneous process.

Lazerli metal yigma yontemi eklemeli imalat yontemlerinden biri olarak ortaya cikmistir. Ozellikle sanayide son urun ciktisindaki malzeme urun hassasiyeti ve maliyet acisindan yasanan problemler bu yontemin gelistirilmesinde ve uzerinde onemle durulmasinda onemli bir rol ustlenmistir. Ancak Lazerli metal yigma yonteminde yontem geregi uygulanan parametrelerden kaynakli dezavantajlari bulunmaktadir. Bu dezavantajlardan birisi ise artik gerilmedir. Artik gerilme imalat sirasinda isinma ve soguma hizlarina bagli olarak, malzeme icerisinde kalan basma-cekme kuvvetlerinin etkisidir. Bu calismada Lazerli metal yigma yonteminde kullanilan proses parametrelerinin artik gerilme probleminin giderilmesi ve elde edilecek urunun kalitesinin artirilmasi uzerindeki etkileri sonlu elemanlar yontemiyle analiz edilmis ve termal sonuclari karsilastirilmistir. Calisma icin Simufact programindan yararlanilmistir. 3 boyutlu tasarim modul icerisine aktarildiktan sonra standart parametreler disindaki deger...

The formation of laser-induced periodic surface structures (LIPSS, ripples) upon irradiation of silicon with multiple irradiation sequences consisting of femtosecond laser pulse pairs (pulse duration 150 fs, central wavelength 800 nm) is studied numerically using a rate equation system along with a two-temperature model accounting for one-and twophoton absorption and subsequent carrier diffusion and Auger recombination processes. The temporal delay between the individual equal-energy fs-laser pulses was varied between 0 and ∼ 4 ps for quantification of the transient carrier densities in the conduction band of the laser-excited silicon. The results of the numerical analysis reveal the importance of carrier generation and relaxation processes in fs-LIPSS formation on silicon and quantitatively explain the two time constants of the delay dependent decrease of the Low-Spatial-Frequency LIPSS (LSFL) area observed experimentally. The role of carrier generation, diffusion and recombination are quantified individually.

Universitas Multimedia Nusantara (UMN) integrates green building principles to enhance environmental sustainability by reducing energy waste and utilizing renewable energy sources. This study conducts a feasibility analysis of installing solar panels in a green open space near building D to supply up to 20% of its electricity needs. PVSyst simulations evaluated different panel orientations (north, south, and east). The results indicated that the installation is currently unfeasible, with a net present value (NPV) of 134,346,450.22 IDR and an internal rate of return (IRR) of -4.64%. The challenges included shading from surrounding buildings, heat buildup, and limited installation space. To improve viability, future installations should focus on sites with minimal shading and explore advanced technologies to enhance efficiency. Additionally, optimizing panel orientation and investigating alternative renewable energy sources suited to UMN’s conditions are crucial. These measures can enhance the effectiveness of solar installations and contribute to overall energy sustainability on campus.

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

To predict chitosan/cotton yarn properties in ring spinning, a particle-level simulation method has been used to simulate the dynamics of the fibers with different initial positions in three-dimensional airflow around counter-rotating cylinders. The results show that the fibers near the cylinder end-face can leave two cylinders' nip and move around the top cylinder, thus form fly waste. It is good to entangle other fibers as this gives the fiber greater bending energy. Compared with cotton fiber, the axial-direction deflections of the tail-ends of chitosan fibers near the cylinder center are much greater, while their bending energies are much lower, thus forming a wide triangle zone and reduced fiber-fiber cohesion force and yarn strength. To demonstrate the simulation results, a series of spinning experiments are completed, which tally with the predictions.

A three-dimensional particle-level simulation method is developed to simulate fiber dynamics in the ring spinning triangle. The fiber is modeled as a chain of beads connected through massless rods, and its flexibility is defined by the stretching, bending and twisting displacements. As the application of the proposed approach, the effects of the chitosan (CS)/cotton (CT) fiber initial position and length on fiber motion and yarn properties are discussed. The deflections of CS fibers along the roller axis are larger compared with those of CT fibers, which will lead to CS migrating outwards in CS/CT blended yarn. The short CS fibers (22 mm) will move toward the top roller surface and shift quickly out of the roller nip, and thus yarn strength is lower. The tailing end of the longest CS fiber (46 mm) will drift off the roller nip, which makes little or no contribution to the yarn strength. For 38 mm length CS fiber, it moves toward the bottom roller surface and is bound into the roller...

The issue of allocating capacity to accommodate emergent surgery cases while scheduling elective patients has major policy implications for Level-1 trauma centers including most large academic medical centers. This is because operating rooms (ORs) are the greatest source of revenues for hospitals, while also being the largest cost centers. However, scheduling ORs, especially at level-1 trauma hospitals, is challenging due to significant uncertainty in the arrivals of patients requiring emergent surgery. When scheduling surgeries, hospitals face a trade-off between the need to be responsive to emergency cases and the need to conduct scheduled elective surgeries as planned. We develop a model that allocates the OR capacity to elective patients so that the emergency patients who arrive randomly can be accommodated without incurring any excessive delays. The objective is to develop a framework for aggregate weekly schedules and generate detailed daily schedules that minimize a weighted sum of the ORs' operating time, idle time, and overtime. Optimization procedures are developed to devise effective block schedules while a rescheduling procedure schedules elective patients who are affected by an emergency arrival. Initially, the procedures are based on deterministic surgery times for the elective patients and then they are extended to stochastic surgery times. We illustrate our methodology on specialized ORs for trauma cases related to neurosurgery. We show that for a given arrival rate of emergency patients, the total expected cost is convex in the weekly load of the elective surgeries scheduled. Numerical experiments are devised to obtain the total expected cost curves for various arrival rates of emergency patients. Using these cost curves the optimal capacity allocation of ORs to elective patients can be determined as a function of the arrival rate of emergency patients.

The growing emphasis on environmental sustainability has drawn considerable attention from both academia and industry practitioners. Factors such as escalating energy costs, heightened environmental degradation, and a burgeoning market demand for eco-friendly practices have compelled businesses to reassess their strategies through a green lens. Given that Lean principles are rooted in optimising operations to minimise waste across design and production processes, their synergy with the green paradigm is evident. However, despite the intuitive connection between Lean methodologies and environmental sustainability, the scholarly exploration of their impact remains largely underdeveloped. This research seeks to bridge this gap by conducting a comprehensive systematic literature review to dissect the current understanding of Lean manufacturing practices and their influence on environmental sustainability performance. The selected papers were meticulously screened and grouped into three clusters using the PRISMA diagram methodology. The primary objective was to discern the tangible effects of Lean practices on eco-efficiency performance and explore integrating Lean manufacturing principles with broader sustainable manufacturing approaches. A structured matrix was created to categorise and visualise the identified impacts gleaned from the initial articles. Nevertheless, the review revealed significant gaps in understanding, particularly regarding the factors that shape the efficacy of Lean manufacturing tools in enhancing eco-efficiency performance. The findings underscore the need for further research to unravel these complexities and delineate the mechanisms through which Lean practices contribute to environmental sustainability. Several avenues for future research have been delineated, focusing on how Lean manufacturing practices can be leveraged to support eco-efficiency performance effectively. While the preliminary findings shed light on the promising intersection between Lean principles and environmental sustainability, they also underscore the imperative for continued scholarly inquiry to unlock the full potential of Lean methodologies in fostering a greener industrial landscape.

This research study sought to explore the influence of executors, implementation tactics and organizational level on strategy formulation and implementation in family owned businesses as observed at Quality Meat Packers Limited .Strategy formulation is the development of a mission and mission, identification of organizational environmental analysis, establishment of objectives, generation of alternative strategies and picking of specific strategies for pursuit of accomplishments. Strategy implementation is the strategy translation into organizational action whilst aiming at the strategic objectives and goals. The relevant theories on the study objectives: including the Strategic Choice Theory, Chandler's Theory of the firm and McKinsey 7s Theory, the conceptual framework, the review of empirical studies, the critique of the reviewed literature and research gaps were captured. The study adopted a descriptive research design in which data was gathered over the period 2020 to 2021. The study is carried out using primary and secondary data. The study utilizes stratified sampling. The target population was 500 personnel of Quality Meat Packers Limited. Questionnaires were used among sampled employees at Quality Meat Packers Limited. The sample size for the study was management members of Quality Meat Packers Limited. 25 of them were top level managers and 40 of them were middle level managers. Data collected was analysed by the use of SPSS and Microsoft Excel. Regression analysis was adopted for estimation of regression coefficients and determination of the models' prediction levels. The results of this study largely concurred with the position that successful strategy formulation and implementation in a family owned business is influenced by implementation tactics, executors and organizational level

Smart factories represent the advancement of manufacturing innovation, where digital technologies, artificial intelligence (AI), and the Internet of Things (IoT) converge to create systems that are interconnected, self-organizing, and highly efficient. At the linchpin of these advancements lies the critical process of production scheduling, a complex task that determines the optimal order of production activities to meet manufacturing goals. Traditional scheduling methods often struggle to keep pace with the dynamic demands of modern manufacturing, leading to inefficiencies, longer lead times, and suboptimal resource utilization. AI-powered production scheduling emerges as a transformative solution, leveraging the capabilities of machine learning, deep learning, and other AI technologies to revolutionize how production activities are planned, executed, and optimized in smart factories. AI-powered production scheduling represents a critical step forward in the evolution of smart factories. By significantly reducing lead times and improving resource utilization, AI technologies offer the potential to reshape the manufacturing landscape, making it more efficient, flexible, and responsive to the needs of the global market. As the field continues to evolve, ongoing research and collaboration between academia and industry will be vital in overcoming existing challenges and unlocking the full potential of AI in manufacturing.

This paper describes a method for analyzing the field penetrating through planes in package power distribution networks. This field can cause excessive noise in the system at resonant frequencies of the package. The effect has been quantified both in the time and frequency domain and compared with measurements. General guidelines have been suggested to suppress this noise by varying the material and physical parameters of the planes.

Simultaneous switching noise (SSN) has become a major bottleneck in high speed digital design. For future systems, modeling SSN can be complex due to the thousands of interconnects that need to be analyzed. This is because a system level modeling approach is necessary that combines the chip, package and board level interactions. This paper presents an efficient method to model the SSN for high speed systems by developing circuit models for the planes and interconnections that can be combined using superposition theory. This approximation is valid at frequencies where skin effect is dominant. Simulation results are compared with the measurements on a test vehicle, verifying the validity of the method. In addition a system has been simulated to compute SSN, showing the application of this method for complex systems.

Risk assessment is essential to making informed decisions on occupational risk prevention. The health and safety conditions of workers can be improved by issuing voluntary certifications, such as ISO 45001. This is particularly important in sectors such as wineries. In 2017 these numbered 4093, representing 14% of the food and drink industry in Spain, of which 290 were in Andalusia. The incidence rate for 2017 in the industrial sector in Spain was 5.264 work accidents with sick leave for every 100,000 affiliated workers, making this the sector with the second highest number of work accidents after that of construction. The study aims to assess the risks in wineries in Andalucía, southern Spain, by analysing the opinions of a group of experts with experience in the sector. The Delphi method was used for this study and was carried out in conjunction with a panel of 11 experts. The results indicated that the most significant workplace risks were those occurring in the production facility, workshop or factory; in terms of occupation, those exposed to the greatest risk were machine operators; regarding the type of work, production, processing and storage posed the highest levels of risk; operating machinery was the physical activity with the highest risk; in the area of causes of accidents, the highest risk was of slipping, tripping and falling; and, finally, with regard to how an accident could occur, the highest level of risk was considered to be contact with electric current.

Risk assessment is essential to making informed decisions on occupational risk prevention. The health and safety conditions of workers can be improved by issuing voluntary certifications, such as ISO 45001. This is particularly important in sectors such as wineries. In 2017 these numbered 4093, representing 14% of the food and drink industry in Spain, of which 290 were in Andalusia. The incidence rate for 2017 in the industrial sector in Spain was 5.264 work accidents with sick leave for every 100,000 affiliated workers, making this the sector with the second highest number of work accidents after that of construction. The study aims to assess the risks in wineries in Andalucía, southern Spain, by analysing the opinions of a group of experts with experience in the sector. The Delphi method was used for this study and was carried out in conjunction with a panel of 11 experts. The results indicated that the most significant workplace risks were those occurring in the production facility, workshop or factory; in terms of occupation, those exposed to the greatest risk were machine operators; regarding the type of work, production, processing and storage posed the highest levels of risk; operating machinery was the physical activity with the highest risk; in the area of causes of accidents, the highest risk was of slipping, tripping and falling; and, finally, with regard to how an accident could occur, the highest level of risk was considered to be contact with electric current.

The optoelectronic properties of ultrananocrystalline diamond films (UNCD) grown using N 2 = 0 and 5% in the deposition gas mixture, are investigated by transient photocurrent measurements under nanosecond light pulses, both in planar and sandwich contact arrangements. Independent of contact configuration and N 2 % value, very similar characteristic times in the 6-7 ns range are detected in the nanosecond range, reflecting a homogeneous distribution of states responsible for such decay times. On a longer time scale, nitrogen addition appears to slow down carrier transport promoting trapping and detrapping processes responsible for single and two power law photocurrent decays in films deposited using N 2 = 5% for sandwich and planar contact arrangements, respectively. Such a result suggests a nitrogen induced transport anisotropy tentatively related to structural modifications occurring at relatively low N 2 %.

A detailed characterization under 90 Sr β-particles and 4.5 MeV protons micro-beam of a singlecrystal CVD diamond-based three-dimensional detector with surface and buried graphite electrodes is presented. Pillar contacts, 300 µm long and 30 µm diameter, were fabricated by using a femtosecond laser operating at 1030 nm wavelength and 400 fs pulse duration. Charge collected under 90 Sr β-particles was measured in front and back irradiation conditions, pointing out that the pillars contribute to the charge collection. Charge collection efficiency (CCE) was measured to be up to 94% under proton beam irradiation. Results of a comprehensive study, including crossedpolarizers imaging, numerical simulation of the electric field distribution, and proton mapping, show that CCE is not affected from the stress induced by the pillar fabrication, and that the electric field strength is high enough to partially compensate for carrier recombination in the defected regions surrounding the pillars.

Manuela Lageiro and Maria Costa-Ferreira1 Bioengineering and Bioprocessing Unit, Department of Biotechnology, National Institute for Industrial Engineering and Technology (INETI), Portugal An enzymatic cocktail was used for the decolorization of process wastewater, containing mainly three reactive azo dyes, from a textile dyeing and printing company. Water sampled from different processing streams and combinations thereof was decolorized to different extents. The decolorization was greatest for C.I. Reactive Black 5, followed by C.I. Reactive Red 158, whereas C.I. Reactive Yellow 27 was the least decolorized. As wastewater from the printing process was inhibitory, the 1 mistirred tank type reactor prototype was installed near the outlet prior to the discharge of wastewater from the printing process. Temperature and pH control systems were installed to ensure optimal enzymatic decolorization, this being about 45 ° C and pH 6.4. The average temperature observed at the reactor was 42.1...

A rotating packed bed (RPB), which creates a high gravity environment by the centrifugal force, is one of the typical process intensification equipment. The cavity zone is an important mass transfer zone of a RPB. However, there have been very few studies to date on the modeling of mass transfer in the cavity zone. In this work, the liquid droplet velocity in the cavity zone was obtained by analysing the images taken by a high-speed camera and correlations for droplet velocity were fitted. Combining the above imaging results and other parameters, a mathematical model was established to predict the mass transfer area of the cavity zone. The mass transfer system of chemisorption of CO 2 into NaOH solution was employed and mass transfer experiments were carried out at various rotational speeds, liquid initial velocities, and outer packing radii. The predicted mass transfer area from the model agreed well with the experimental data within a deviation of ±20%.

The heat generated during the welding of stainless steel results in the oxidation of the surface that, apart from aesthetics, adversely affects its corrosion property too. This communication reports the successful removal of heat tint generated by the gas tungsten arc welding process off a stainless steel surface in addition to an improvement in its pitting corrosion resistance by exposure to the emission of a nanosecond pulsed fiber laser. The laser cleaning experiments, conducted with six different laser pulses having different temporal shapes and duration that varied from 20 to 1020 ns, revealed that removal of the weld heat tint was possible in all conditions provided the effective laser fluence exceeded a definite threshold value. This threshold value, in turn, was found to increase with an increase in pulse duration. The laser cleaned specimens were subsequently analyzed for surface morphology, roughness, and pitting corrosion resistance. The pitting corrosion resistance of th...

The heat generated during the welding of stainless steel results in the oxidation of the surface that, apart from aesthetics, adversely affects its corrosion property too. This communication reports the successful removal of heat tint generated by the gas tungsten arc welding process off a stainless steel surface in addition to an improvement in its pitting corrosion resistance by exposure to the emission of a nanosecond pulsed fiber laser. The laser cleaning experiments, conducted with six different laser pulses having different temporal shapes and duration that varied from 20 to 1020 ns, revealed that removal of the weld heat tint was possible in all conditions provided the effective laser fluence exceeded a definite threshold value. This threshold value, in turn, was found to increase with an increase in pulse duration. The laser cleaned specimens were subsequently analyzed for surface morphology, roughness, and pitting corrosion resistance. The pitting corrosion resistance of th...

Perkembangan dunia industri manufaktur dan jasa semakin meningkat pesat dari waktu ke waktu sehingga setiap pelaku industri harus siap berkompetisi dengan kompetitornya. Oleh karena itu masalah dan faktor-faktor yang berhubungan dengan peningkatan produktifitas semakin menonjol dan perlu untuk diteliti. Penelitian ini dilaksanakan di industri perakitan mobil Tamiya.Pada penelitian ini yang diteliti yaitu metode kerja dan layout kerja operator, kemudian dilakukan usulan perbaikan dengan menerapkan metode 5S pada lingkungan kerja. Setelah dilakukan pengolahan data dan pembahasan terhadap data pengukuran waktu perakitan, analisis metode 5S pada layout baik sebelum dan sesudah usulan perbaikan dan jumlah hasil produksi masing-masing layout kerja ternyata jumlah hasil produksi pada layout sesudah usulan perbaikan dilakukan mengalami peningkatan dibandingkan layout sebelum usulan perbaikan dilakukan. Hal ini dibuktikan dengan indeks produktifitas yang meningkat dari sebelum usulan perbaikan dilakukan dimana indeks produktifitas sebelum usulan perbaikan adalah sebesar 97,5 %, sedangkan indeks produktifitas pada layout kerja sesudah usulan perbaikan 115 %. Oleh karena itu bisa dikatakan bahwa micromotion study dan metode 5S telah membawa efek yang baik bagi perbaikan metode kerja dengan menghilangkan gerakan tidak efektif dan menata lingkungan kerja agar lebih bersih dan rapi sehingga meningkatkan produktifitas kerja operator.

The development of manufacturing and service industries is increasing rapidly from time to time so that every industry player must be ready to compete with his competitors. Therefore the problems and factors associated with increasing productivity are increasingly prominent and need to be examined. This research was conducted in Tamiya auto assembly industry.In this study investigated the work method and operator work layout, then performed the proposed improvement by applying the 5S method on the work environment. After data processing and discussion of assembly time measurement data, 5S method analysis on layout both before and after the proposed improvement and the number of production results of each work layout was the amount of production in the layout after the proposed improvements made increased compared to the layout before the proposed improvementdo.This is evidenced by the increased productivity index from before the proposed improvement donewhere the productivity index ...

Maintenance management of an industrial plant has been always a complex activity. Nowadays
Computerized Maintenance Management Systems (CMMSs) help to organize information and thus to
carry out maintenance activities in a more efficient way. The emergence of new ICT has increased also the
use of Condition Based Maintenance (CBM) systems and the application of Reliability Centred
Maintenance (RCM) analysis. Each system is proved to provide benefits to the maintenance
management. However when all the systems are adopted, the lack of integration among them can
prevent the maximum exploitation of their capabilities. This work aims at fulfilling this gap, proposing
an e-maintenance integration platform that combines the features of the three main systems. The
methodology and the reference open standards used to develop the platform are exposed. UML-BPMN
diagrams represent the emerging algorithms of

PurposeTo compare the performance of a new hybrid manufacturing system (HMS) with a conventional cellular manufacturing system (CMS). The hybrid system is a combination of the cellular manufacturing and job shop.Design/methodology/approachA hypothetical manufacturing facility with eight machines and 20 parts is used as a case. Simulation models are developed for two manufacturing systems. A multi‐factor comparison is carried out to test the performance of the systems under different scenarios.FindingsIt was found that group scheduling rules (GSR) and the manufacturing system design factors have significant impact on the performance of the system. In particular, the hybrid system shows its best performance when the MSSPT GSR is applied, whereas the cellular system is superior when DDSI is implemented. The results also demonstrate that, by adding non‐family parts to the production schedule of the HMS, significant benefits in the performance measures can be attained.Research limitation...