Manufacturing Performance Research Articles

Material extrusion additive manufacturing of zirconia: from filament characterisation to Weibull statistics

PurposeThis study aims to investigate the performance of filament-based material extrusion additive manufacturing (MEX), combined with debinding and sintering, as a novel approach to manufacturing ceramic components.Design/methodology/approachA commercial ZrO2 filament was selected and analysed by infra-red (IR) spectroscopy, rheology and thermo-gravimetry. The influence of the print parameters (layer thickness, flow rate multiplier, printing speed) and sintering cycle were investigated to define a suitable printing and sintering strategy. Biaxial flexure tests were applied on sintered discs realised with optimised printing strategies, and the results were analysed via Weibull statistics to evaluate the mechanical properties of printed components. The hardness and thermal conductivity of sintered components were also tested.FindingsLayer thickness and flow rate multiplier of the printing process were proved to have significant effect on the density of as-printed parts. Optimised samples display a sintered density >99% of the theoretical density, 20% linear sintering shrinkage, a characteristic flexural strength of 871 MPa with a Weibull modulus of 4.9, a Vickers hardness of 12.90 ± 0.3 GPa and a thermal conductivity of 3.62 W/mK. Gyroids were printed for demonstration purposes.Originality/valueTo the best of the authors’ knowledge, this work is the first to apply biaxial flexure tests and Weibull statistics to additively manufactured MEX zirconia components, hence providing comparable results to other additive technologies. Moreover, fractography analysis builds the connection between printing defects and the fracture mechanism of bending. This study also provides guidelines for fabricating high-density zirconia components with MEX.

The geometry uniformity parameters effect on the dynamic behaviour of trapezoidal beam

Understanding the delicate interplay between geometric design principles and dynamic responses is vital for numerous engineering applications because it allows optimization of structural integrity and performance for manufacturing and special use of this structures. In this study, a complete numerical analysis is undertaken to investigate how differences in geometric parameters impact the structural behaviour of a cantilever smart trapezoidal beam, giving useful insights for engineering applications. The beam consists of a host structure made of aluminum couple with two piezoelectric layers on its top and bottom surface. For such purpose, the study a 3D finite element model has been implemented in ANSY APDL and applied by Matlab we used the interfaces between the two software, considering that the beam changes its form in the axial direction following polynomial based function. The function takes two geometric parameters as an input which are the tapering ratios and the degree of non-uniformity. The beam is then subjected to a harmonic based excitation and the effect of changing tapering ratios and the degree of non-uniformity is analyzed., allowing analysis of the effects of altering tapering ratios and the degree of non-uniformity The results led to a conclusion that just by manipulating the mentioned parameters a considerable changing in the fundamental frequency and the amplitude has been noticed. Addition our numerical analysis shows that small changes to the tapering ratios and degree of non-uniformity have a considerable influence on the behavior of cantilever smart trapezoidal beams. These discoveries add to continuing research in smart materials, paving the road for creative engineering solutions.

Evaluation of sustainable manufacturing performance – A case illustration with multistakeholder perspective

Increasing awareness on achieving the targets of sustainable development goals led to the various discussions on sustainability in manufacturing applications. Sustainable manufacturing has been considered as one of the key factors for achieving sustainable consumption and production. Considering the advantages, sustainable manufacturing has been discussed with various perspectives in order to improve the sustainable manufacturing performances. This study considers one of the perspectives where other studies are limited within the context of sustainable manufacturing performances, multi-stakeholder perspectives. The sustainable manufacturing performances has been collected and evaluated with multi criteria decision making methodology, best worst method. The three multi stakeholder perspectives have been considered for this study which includes manufacturer perspective, customer perspective and government perspective. The collected sustainable manufacturing performances were evaluated based on these different multi-stakeholder perspectives, in order to understand the similarities and differences among multiple stakeholders in the implementation of sustainable manufacturing through its performances. The detailed discussion of obtained results was explored and acknowledged with existing literature support along with the response from case industrial managers. The similarities and differences of opinion among different stakeholders has been explored to provide fruitful contributions to both academic and scientific community. The key managerial implication of this study is that assisting the industrial managers to focus on influential sustainable manufacturing performances instead of focussing less influential ones based on the opinions of different stakeholders.

The Influence of Organizational Commitment, Work Environment, Work Discipline, and Motivation on Employee Performance in Manufacturing and Assembly of Electronic Components

This research aims to determine and analyse the influence of Organizational Commitment, Work Environment, Work Discipline and Motivation. This type of research is quantitative with a population of 76 respondents. Questions are given using a questionnaire with the Google Form technique. The data analysis methods used are Descriptive Test, Validity Test, Reliability Test, Classical Assumption Test, Multiple Analysis and Determination (????2). The results of data analysis using multiple regression and hypotheses using the SPSS program and it can be seen that Organizational Commitment has a significant effect on employee performance, Work Environment does not have a significant effect on employee performance, Work Discipline has a significant effect on employee performance, Motivation has a significant effect on employee performance, and systematic testing Simultaneously shows that Organizational Commitment, Work Environment, Work Discipline and Motivation have a significant effect on Employee Performance.

Ethylene control in fruit quality assurance: A material science perspective

AbstractThe waste of resources associated with fruit decay is rapidly spreading globally, threatening the interests of relevant practitioners and the health of consumer groups, and demanding precise solutions. Controlling fruit ripening through ethylene regulation is one of the most important strategies for providing high‐quality fruits. However, current materials for ethylene regulation still have difficulty realizing their application potential due to high manufacturing costs and performance deficiencies. In this review, the ethylene‐controlled release materials for ripening based on molecular encapsulation and the ethylene scavengers for preservation based on mechanisms such as oxidation, photodegradation, and adsorption are presented. We discuss and analyze a wide range of materials in terms of mechanism, performance, potential of applicability, and sustainability. The ethylene release behavior of encapsulating materials depends on the form in which the ethylene binds to the material as well as on environmental factors (humidity and temperature). For ethylene scavengers, there are a variety of scavenging mechanisms, but they generally require porous materials as adsorption carriers. We highlight the great opportunity of designing soft crystalline porous materials as efficient ethylene adsorbent due to their unique structural properties. We present this review, including a summary of practical characteristics and deficiencies of various materials, to establish a systematic understanding of fruit quality assurance materials applied to ethylene regulation, anticipating a promising prospect for these new materials.

The adoption of Industry 4.0 technologies by using the technology organizational environment framework: The mediating role to manufacturing performance in a developing country

AbstractThe study aspires to identify the factors conditioning the adaptation of the fourth industrial revolution (4IR) within the manufacturing industries in Bangladesh, embracing Industry 4.0 (I4.0) technology led by the technology‐organizational‐environment (TOE) framework that links a number of conditioning variables in the manufacturing industries of Bangladesh. I4.0 is going to drastically change the landscape of the extended TOE framework to relate demographics with research variables for implementing I4.0 technology in a developing country. The findings of the study are analyzed using SMART PLS SEM 4.0 and SPSS 29 in order to diagnose technological contexts (IT resource availability, technology readiness, and relative advantage), organizational contexts (strategy and leadership, organizational capabilities, and technology infrastructure), and environmental contexts (market pressure, government support, and technology innovation decision making). The study's data, which were collected with a bootstrap confidence range of 95%, offered evidence in favor of both proposed mediating effects. A statistically significant indirect effect of adaptation of I4.0 technology on manufacturing/industry performance was seen in the analysis. This study is conducted to examine the mediating function of manufacturing performance, which enhances the comprehensiveness of the study. Through the application of the TOE framework, this study investigates the impact of I4.0 technology adoption on manufacturing performance. The theoretical framework of the study has been validated by the TOE model, which aims to heighten manufacturing performance by integrating I4.0. The practical implications of this study, organizations, governments, and practitioners engaged in the implementation of I4.0 technologies within developing nation contexts.

Manufacture and Analysis Performance of Injection Device System 4 Stroke Engine Againts Emissions

Manufacture and Analysis Performance of Injection Device System 4 Stroke Engine Againts Emissions

The AI Era: Innovations, Challenges, and Applications

In the coming years, intelligent machines are poised to augment or replace human abilities across multiple domains. Artificial intelligence (AI), a subset of computer science, demonstrates machine or software intelligence. Over the past two decades, AI has significantly bolstered performance in manufacturing, services, and education. The proliferation of AI has led to the emergence of expert systems, revolutionizing problem-solving in education, engineering, business, medicine, and weather forecasting. Its widespread application has notably improved quality and efficiency in various sectors. This paper offers a concise overview of AI, emphasizing its significance in education, encompassing its definition, search methodologies, breakthroughs, and future prospects.

Reimagining Local Broadcasting Unveiling Dynamic Communication

This qualitative study delves into the communication styles of broadcasters and listeners within the Lontong Balap RRI Surabaya program, aiming to fill gaps in understanding communication dynamics in local radio contexts. Data collection involved non-participant observation and interviews, with purposive sampling selecting informants from both broadcaster and listener demographics. Findings reveal a predominant equalitarian communication style, fostering direct interactions and natural engagement between broadcasters and listeners. The program serves to revive local culture while providing information and entertainment, showcasing the significance of relatable language and direct engagement in enhancing audience participation and program effectiveness within local radio broadcasts. Hghlight: Efficient Inventory System: PT. Perdana Sukses Makmur demonstrates effective inventory management practices. Internal Control Challenges: Addressing function combination enhances organizational oversight. Production Efficiency Implications: Refining internal controls enhances manufacturing performance. Keywoard: Inventory Management, Internal Control, Manufacturing Company, Qualitative Study, Indonesia

Enhancing Operational Performance through Green Manufacturing Practices: Case Studies from TQM Implementation in the Indonesian Industrial Sector

Enhancing Operational Performance through Green Manufacturing Practices: Case Studies from TQM Implementation in the Indonesian Industrial Sector. This study explores the impact of environmentally friendly manufacturing practices on the performance of the Indonesian industrial sector, with a specific focus on Total Quality Management (TQM) implementation. The research aims to evaluate the application of green manufacturing, examine its effects on operational parameters, identify key success factors, and provide strategic recommendations. A mixed-methods approach, comprising surveys, interviews, and case studies, was employed to gather quantitative and qualitative data from various industries in Indonesia. The results of the study indicate a positive correlation between green manufacturing practices and performance indicators. High-performing companies achieved cost savings, resource optimization, and greater energy efficiency. Success factors included employee involvement, technology adoption, and regulatory compliance. In conclusion, integrating green manufacturing within the TQM framework is crucial for sustainable industrial development. The study emphasizes the need for proactive and collaborative decommissioning strategies and continuous improvement cycles.

Using Taguchi method and gray relational analysis to enhance manufacturing performance in photopolymerization

Using Taguchi method and gray relational analysis to enhance manufacturing performance in photopolymerization

A Multivariate Performance Analysis of the Plastics Manufacturers: Comparative Analysis of European Regions

Abstract This study evaluates the economic performance of plastics manufacturers in European regions (e.g., Western, Southern, Central and Eastern Europe, and the Baltic States) between 2017 and 2020 based on data from 3,372 companies using multivariate correspondence analysis (MCA) and Welch’s test. They were analyzed according to the indicators of profitability, sales (or turnover), employment, and total assets. The results of MCA show that Central and Eastern European companies are absolute leaders in terms of profitability. While Southern European companies have the highest total assets, their sales and profitability are lower compared to other regions. We found that Western European companies lead in terms of turnover and that the Baltic region is roughly on par with Central and Eastern European countries in terms of profitability and employment. These differences were also tested using the pairwise Welch’s test, which revealed highly statistically significant differences, especially in turnover and total assets. The results also show that profitability levels are similar regardless of company size, while sales and total assets are significantly different across European regions. These findings on plastics manufacturers in different European regions are crucial to help policymakers and industry leaders make informed decisions to address economic performance, investment and environmental concerns, and to develop sustainable solutions for the plastics industry.

K-ion preintercalated MnO2 nanorods as a high-rate cathode material for aqueous zinc-ion batteries

The integration of Zn/α-MnO2 in aqueous zinc-ion batteries (ZIBs) has emerged as a promising avenue owing to their eco-friendliness, facile manufacturability, cost-effectiveness, low flammability, and commendable electrochemical performance. However, the intrinsic limitation in the rate capability of α-MnO2 constitutes a significant impediment to its practical application. In this study, we introduce K-ion preintercalated nanorods (K-MnO2-NR) with a diameter of approximately 10 nm as a cathode material for ZIBs. The synthesis of K-MnO2-NR entails a facile one-step electrochemical participation method, whereby K-ion are electrochemically intercalated into the tunnel-structured α-MnO2. The incorporation of K-ion serves a dual purpose of enhancing the electrical conductivity of manganese oxides and stabilizing the tunnel structure. Consequently, K-MnO2-NR manifests exceptional rate capability, exhibiting a specific capacity of 222 mAh g−1 at 2 A g−1, coupled with outstanding cycling stability (with negligible capacity decay observed over 1450 cycles at 2 A g−1). The facile and scalable synthesis process underscores its potential for large-scale production and eventual commercialization in pouch cells for energy storage applications.

Utilization of Data Analytics to Enhance Operational Efficiency in Manufacturing Companies

In the digital era, manufacturing industries confront challenges like heightened global competition and intricate production processes, urging them to boost efficiency and productivity. Amidst these circumstances, Big Data emerges as a pivotal opportunity to enhance manufacturing performance. Big Data, characterized by vast volumes of data, utilizes advanced data mining to machine learning techniques for analysis. Data analytics, an interdisciplinary field, profoundly impacts manufacturing operations, enabling deeper insights into production processes. By analyzing production data, companies identify inefficiencies, streamline workflows, and enhance operational efficiency and productivity. Predictive maintenance through sensor data analysis prevents machine failures, while logistics data analysis optimizes supply chains and inventory management, reducing costs and enhancing competitiveness. However, implementing Big Data analytics presents challenges such as rapid data growth, diverse data sources, real-time insights, skill shortages, and data fragmentation. Overcoming these hurdles requires robust technology, skilled personnel, and effective data management strategies. Examples of Big Data analytics applications include customer behavior analysis by Amazon and Netflix, fraud detection in insurance, and urban mobility optimization. Success factors in data analytics implementation include effective data-driven communication, technology integration, and skill enhancement. In conclusion, implementing Big Data Analytics in manufacturing promises significant benefits in operational efficiency, product quality, and competitiveness. Overcoming challenges necessitates robust strategies and consideration of ethical and security issues, ensuring responsible data usage. With a deep understanding of Big Data Analytics, manufacturing companies can leverage this technology to achieve higher efficiency and competitiveness in the global market.

The value of “green label”: green factory and corporate ESG performance

ABSTRACT Green manufacturing and corporate ESG performance are two vital issues related to sustainable development. Utilizing manually collated data of green factory, publicly listed company data and corporate ESG scores disclosed by the Bloomberg database, this paper adopts a difference-in-difference approach to explore the impact of green manufacturing on corporate ESG performance. The empirical results demonstrate that green manufacturing significantly enhances corporate ESG performance by expanding green investment and alleviating financing constraints. Further analysis indicates that green manufacturing plays a more crucial role in improving corporate environmental performance and social responsibility. The findings offer valuable insights for refining government environmental regulatory tools and for corporations aiming to enhance their ESG performance.

Optimizing manufacturing firm performance in Indonesia through strategic orientation and servitization

This study aims to investigate factors influencing servitization and firm performance within Indonesian national manufacturing companies, focusing on export-oriented entities such as automotive, electronics, textile, and food processing industries. Strategic orientations – market, technology, service, and learning – are investigated as key dimensions guiding firms’ strategic decisions amidst dynamic business environments. A comprehensive survey involving 100 companies representing a diverse spectrum of the Indonesian manufacturing sector is conducted. These companies encompass a range of statuses, including joint ventures (12%), multinational companies (2%), and national companies (86%). Through a purposive sampling strategy, representation across different company types is ensured to capture the breadth of perspectives within the industry. The quantitative approach involves surveying managers across various organizational levels, including top-level executives, middle managers, and front-line supervisors. Input from different managerial tiers is solicited to understand strategic orientations and their impact on firm performance. Data analysis, employing validation, descriptive statistics in MS Excel, and inferential statistics using Smart PLS yields significant insights. Market, service, and learning orientations emerge as influential factors in both basic and advanced services (p < 0.05), while technology orientation lacks statistical significance. Notably, market orientation significantly impacts advanced services (p < 0.05). Furthermore, the findings underscore the significant influence of service provision on firm performance across both basic and advanced services (p < 0.05). The critical role of strategic orientations, encompassing technology adoption, market positioning, service delivery, and organizational learning, in driving servitization and enhancing firm performance in Indonesian manufacturing is emphasized.

Sustainable biocomposites from pyrolyzed lignin and recycled nylon 6 with enhanced flame retardant behavior: Studies on manufacturing and quality performance evaluation

AbstractThe recycled nylon (RN)‐based biocomposites were fabricated by adding 25% lignin biocarbon. Lignin was pyrolyzed at 300, 600, and 900°C to produce Lig300, Lig600, and Lig900 biocarbon (BioC) samples, respectively. Higher functionality of Lig600 (unlike Lig900) allowed for improved interfacial interaction with the polar nylon matrix. Mechanical properties were further enhanced for RN_Lig600 composite with enhanced flexural and tensile strength by 18% and 8%, respectively, compared to neat polymer (RN). RN_Lig900 composite showed enhancement in tensile and flexural modulus by 32.6% and 51.1%, respectively, compared to RN. Incorporation of Lig900 in RN matrix resulted in 77.9% reduction in burning rate compared to RN. These results show the potential of lignin BioC as a filler in RN composites for flame retardant applications and mechanical enhancement, such as in the automotive industry.Highlights Effect of pyrolysis temperatures (300, 600, and 900°C) on lignin biomass. Composites prepared from recycled polyamide 6 from carpet waste and biocarbon. Improved interfacial adhesion of 600°C biocarbon with recycled nylon matrix. Enhanced thermal, mechanical properties, reduced flammability of biocomposites. Sustainable biocomposites with 900°C biocarbon reduced burning rate by 78%.

Understanding and mitigating temperature-induced agglomeration in silica-based chemical mechanical planarization (CMP) slurry storage

This study explores the impact of temperature on silica particle agglomeration in Chemical Mechanical Planarization (CMP) slurries during storage. Slurries were stored at 15 °C, room temperature, and 45 °C, and analyzed. ATR-FTIR, RAMAN, SEM, zeta potential, and LPC were employed providing qualitative and quantitative data on slurry stability and agglomeration tendencies. Elevated temperature storage significantly increased agglomeration and large particle counts with particle counts value of ∼1.2×107 Part./ml, likely due to water molecule dehydration leading to destabilization. Low-temperature storage also induced agglomeration but to a lesser extent with particle counts the value of ∼4.0×106 Part./ml compared with the RT (∼2.0×106 Part./ml). Short-term storage yielded soft agglomerates with LPC of ∼(2.0–4.0)×106 Part./ml, while long-term high-temperature storage led to hard agglomerates with LPC of ∼3.0×107 Part./ml. The ATR-FTIR and Raman analysis indicate that the spectroscopic features of the original slurry exhibited changes upon variation of storage temperature from RT to 15 and 45 °C. The study also explored the reversibility of agglomeration post-treatment, indicating a potential mitigation pathway. The results demonstrated an inverse relationship between temperature and dissolved oxygen (DO) in silica slurries. For example. the curves depict a decrease in oxygen content from ∼10 ppm at RT to 7 ppm at 45 °C with increasing aging time. A mechanism outlining the temperature and aging-induced agglomeration was proposed, linking temperature fluctuations and thermodynamic aspects to colloidal stability. These findings offer a robust understanding of temperature-induced agglomeration in silica-based CMP slurry storage, paving the way for developing strategies to alleviate these issues and ensuring consistent CMP performance in semiconductor manufacturing.

Intelligent parameters reconfiguration system for enhancing machine tools sustainability using real-time data-driven: an experimental cutting speed investigation

ABSTRACT Industrial manufacturing is not trivial and complex since there are dimensional and tolerance product changes, differences in raw material and variations in machine models. Hence, this research proposes an Intelligent Parameters Reconfiguration System (IPRS) approach for enhancing manufacturing performance and extending cutting tool lifespan through detailed machining parameter setup. The approach joins real-time data acquisition and cutting-edge machine learning techniques to improve the turning machining setup. This research uses related works to conceptualise the IPRS structure in four main steps: machining sensing, data acquisition, data processing and parameters prediction, and automatic machine reconfiguration. The approach enabled dynamic adjustments in cutting speed based on predicted wear, resulting in a notable reduction of 5.6 minutes in manufacturing time and an improvement of 0.2 µm in surface finish. However, it is important to highlight that the experimental solution evaluation was carried out in a controlled scenario using a potentiometer to control the cutting speed on CNC lathes. Therefore, the applicability and scalability of the solution in a real scenario have significant limitations, and the cutting speed control must have direct integration with the machine’s numerical control. As future research, the IPRS approach should consider other influential parameters like cutting depth and feed rate.

Performance Measurement Integration And Performance Of Manufacturing Firms in Rwanda

Rwanda's manufacturing industry is essential to the country's economic growth and employment generation. Achieving sustainable development and global competitiveness necessitates the integration of performance assessment effectively. This entails measuring and optimizing organizational performance, especially in supply chains, using a variety of measures. Global market trends and resource limitations are two ongoing challenges that emphasize the necessity for reliable measuring methods. In order to give policymakers and business practitioners useful information, this study aims to assess the effect of performance measurement integration on manufacturing company performance in Rwanda, concentrating on important industries and geographical areas. Expectancy Theory and the Balanced Scorecard Framework (BSC), two important theoretical frameworks related to performance measurement integration in manufacturing businesses, are examined in the literature study. According to expectation theory, people are driven by their conviction that performance, effort, and results are all related. The BSC provides a strategy-based framework for decision-making at various organizational levels. It was created by Kaplan and Norton. The significance of integrating performance assessment in order to increase productivity, quality, customer happiness, and decision-making for small and medium-sized enterprises (SMEs) is underscored by empirical research. Performance in manufacturing is evaluated and optimized via the use of a variety of instruments and methods, including the BSC and KPIs. 
 The study methodology utilized a quantitative analytic strategy with an explanatory approach to comprehend the relationship between manufacturing company performance and supply chain integration. The research philosophy was shaped by positivism, which prioritized quantitative approaches. Semi-structured questionnaires were used to gather data from 213 manufacturing companies; 94% of the respondents answered the questions. The integration of performance measurement has been found to have a favorable influence on the performance of manufacturing organizations through effective communication, information exchange, and strategic supplier relationships. These findings were supported by descriptive statistics. The findings showed a positive relationship between measurement integration and company performance, with integration accounting for 49.9% of the variance in performance. The results showed that efficient decision-making and information exchange among supply chain participants were influenced. Notably, framework agreements with key suppliers were frequently used in emergency situations. The functions of logistics companies, funders, governments, media, and security personnel in relief efforts were emphasized using qualitative analysis. Issues with inadequate coordination and information exchange were noted. Enhancing IT infrastructure, adopting emerging technologies, collaborating with many stakeholders, and establishing legal frameworks for production readiness are among the recommendations. The study emphasizes how crucial technology, collaboration, and integration are to maximizing the performance of industrial firms and disaster relief in Rwanda.