Increase Production Efficiency Research Articles

Determine the Level of Using Management by Objectives Method in Hospitals Ali Al-Ruwaie

Background: Background: Management by objectives has a greater role for employees in setting goals, positively affecting their performance and commitment to the hospital. It provides each employee with a clear set of tasks to help achieve them. Objectives: To evaluate the extent to which the management method of objectives and feedback is being utilized in Dr. Ali Al-Ruwaie Hospital for Psychiatric and Mental Diseases. Additionally, the study aims to determine the level of trust and participation between the hospital's management and subordinates. Methodology: A cross-sectional study was conducted for a random sample in Dr. Ali Al-Ruwaie Hospital for Psychiatric and Mental Diseases, Benghazi-Libya, and the number of employees was 115. We used a two-part questionnaire to collect data: Part I: Asking the physician's demographic characteristics (gender, age, qualifications, years of experience, education level...etc.). The second part: using the method of management by objectives in the hospital, perceptions, trust and participation between the boss and subordinates, feedback between the boss and subordinates, and commitment of subordinates in achieving goals. Results: A total of 99 employees were recruited to assess the level of using the management by goals method in Dr. Ali Al-Ruwaie Hospital. The arithmetic averages ranged between 3.06 to 4.72, with a general arithmetic mean of 3.94, indicating a high level of practice in the hospital. The dimension of "commitment of subordinates to achieving the goal" ranked first with an arithmetic mean of 4.725 and a standard deviation of 0.752, showing a high level of use. The trust dimension between the subordinate chief came in second with an arithmetic mean of 4.308 and a standard deviation of 0.646, also indicating a high level of use. The sharing between the boss and the subordinate ranked third with an arithmetic mean of 3.716, a standard deviation of 0.610, and an average level of use. Lastly, the feedback dimension ranked fourth with an arithmetic mean of 3.066 and a standard deviation of 0.587, also showing an average level of use. Conclusion: To improve the quality of management in hospitals and increase production efficiency in various service units, it is recommended to implement the management by objectives method. This modern scientific method has proven to yield positive results for all parties involved and will help improve the standards of citizens.

ANALISIS SENSITIVITAS PENURUNAN WAKTU PRODUKSI UNTUK MEMAKSIMALKAN PRODUK JADI SEKTOR KONSTRUKSI DENGAN MEMPERTIMBANGKAN KESEIMBANGAN LINTASAN

In simple terms, optimal allocation of resources will undoubtedly increase production efficiency, which in turn will increase the company's profit. The track balance (Assembly Line Balancing/ALB) aims to distribute the workload among work stations. The object of this research is the balance of the production line and workload in the girder production process. This study emphasizes the sensitivity analysis on reducing working time. Sensitivity analysis was conducted to evaluate the parameters that affect operational flexibility and productivity levels. The decrease in processing time on the largest work element will affect the increase in output. In this case, the processing time on the work element waiting for dry cast will be reduced by 10 minutes in each scenario. In the 8th scenario, the processing time of the working elements waiting for the dry cast is 80 minutes. In other words, the resulting output is 6 units, while idle time drops to 150 minutes. This study recommends reducing the processing time of working elements waiting for dry cast to be 80 minutes.

Future directions in well intervention: A conceptual exploration of emerging technologies and techniques

Well intervention plays a crucial role in the lifecycle of oil and gas wells, encompassing a range of activities aimed at maximizing production, enhancing well integrity, and mitigating risks. This abstract explores the future directions of well intervention, focusing on emerging technologies and techniques that are shaping the industry's approach to well management. The abstract begins by discussing the importance of well intervention in the context of evolving industry trends and challenges, such as the need to maximize recovery from mature fields, improve operational efficiency, and reduce environmental impact. It then provides an overview of the key themes that will define the future of well intervention, including digitalization, automation, and sustainability. Digitalization is transforming well intervention through the use of advanced data analytics, artificial intelligence (AI), and digital twins. These technologies enable real-time monitoring and analysis of well performance, allowing operators to optimize production, predict equipment failures, and enhance reservoir management. Automation is also revolutionizing well intervention by enabling remote operation of intervention tools and robotics, reducing the need for human intervention in hazardous environments. Sustainability is another key theme driving future directions in well intervention, with operators increasingly focused on reducing the environmental impact of well operations. This includes the development of environmentally friendly intervention fluids, the use of renewable energy sources for powering intervention equipment, and the adoption of green completion techniques. The abstract concludes by highlighting the implications of these future directions for the oil and gas industry, including the potential for increased production efficiency, reduced costs, and improved environmental performance. It calls for collaboration between industry stakeholders, research institutions, and government agencies to drive innovation and ensure the long-term sustainability of well intervention practices. Overall, this abstract provides a conceptual exploration of the future directions in well intervention, offering insights into how emerging technologies and techniques are reshaping the industry's approach to well management. his paper will offer a conceptual exploration into the future of well intervention, focusing on emerging technologies and techniques that could revolutionize the field. It will discuss potential impacts on efficiency, safety, and environmental sustainability, providing a theoretical basis for the integration of these advancements in practical settings. Keywords: Future Directions, Well Intervention, Exploration, Emerging Technologies, Techniques.

Techno-economic needs assessment for a sustainable novel solar panel production system

Techno-economic needs assessment for an automated solar panel production system is presented. Solar energy, a rapidly growing renewable energy source, has the potential to meet a significant portion of the world's energy needs. Solar panels, the key component of solar energy systems, there are produced in a major industry. Automated solar panel production systems offer the potential to increase production efficiency and reduce costs. The study outlines key factors necessary for successful establishment and operation of an automated solar panel production factory, including market analysis, financial projections, operational strategies, and sustainability initiatives. The market analysis through examination global trends in the solar energy market, identifying growth trends, potential competitors, and target customer segments. The study used a five-step methodology to assess needs, identifying major requirement such as the application of high-speed and precision manufacturing equipment, investment in reliable and efficient manufacturing processes, and development of cost-effective manufacturing methods. The study’s results highlight several key economic benefits of automated solar panel production, including increased production efficiency, reduced labor costs, and improved product quality. The findings are valuable to various stakeholders, including government officials, business leaders, and community members, informing decisions regarding solar industry development and new manufacturing facilities in specific regions. The paper recommends the use of eco-friendly manufacturing processes, utilization of recyclable materials, and adoption of energy-efficient automated technologies to minimize the carbon footprint of solar panel production.

IoT-enabled smart farming with Industry 5.0

Due to increasing advancements in the field of technology the agricultural sector is experiencing a drastic change, this paradigm shift is the result of integrating technologies like Industry 5.0, Society 5.0, Internet of Things (IoT), Artificial Intelligence (AI), and Remote Sensing. The integration of these technologies helps in multiple aspects such as IoT sensors help in real-time data monitoring which includes parameters such as soil conditions, meteorological aspects„the valuable insights about overall crop health, and also help in promoting informed decision-making in agriculture. Cognitive systems of Industry 5.0, revolutionize manufacturing processes, enabling predictive maintenance, real-time data analyses, and autonomous decision-making for increased production efficiency. Implementing digital twin technology further boosts this transformation process by creating dynamic representations of agricultural systems. Digital twins simplify complex interactions for farmers by integrating data obtained from diverse sources. This paper explores the relationship between Industry 5.0, smart farming practices, implementation of the latest techniques like IoT, and digital twins, understanding their impact on precision agriculture, sustainable farming, and efficiency. In conclusion, this study demonstrates how Industry 5.0 technologies, including digital twin technology, possess the potential to revolutionize agricultural operations, enhance crop yields, foster sustainability, and prepare agriculture for the challenges of a rapidly changing global environment.

ADVANCED BUSINESS ANALYTICS IN TEXTILE & FASHION INDUSTRIES: DRIVING INNOVATION AND SUSTAINABLE GROWTH

This research paper explores the strategic implementation of advanced business analytics within EcoFashions Ltd., a mid-sized company in the textile and fashion industry. The central question it addresses is: How can a specific company leverage advanced analytics in the fashion sector for sustainable growth? Through a qualitative case study approach, the research examines the strategic implementation of analytics at EcoFashions to enhance operational efficiency, drive innovation, and promote sustainability. The findings reveal that the integration of analytics at EcoFashions led to a 25% reduction in material waste and a 15% increase in production efficiency, while also fostering product innovation responsive to market trends. These outcomes not only highlight the potential of business analytics to transform traditional practices within the fashion industry but also suggest that other firms can adopt similar strategies to achieve substantial improvements in sustainability and operational performance. The paper concludes with reflections on the limitations of a single case study and proposes directions for future research to validate and expand upon these findings across the broader industry. This study contributes to understanding how data-driven strategies can facilitate significant sector-wide advancements in sustainability and innovation in the textile and fashion industries.

Enhanced upgrading of lignocellulosic substrates by coculture of Saccharomyces cerevisiae and Acinetobacter baylyi ADP1

BackgroundLignocellulosic biomass as feedstock has a huge potential for biochemical production. Still, efficient utilization of hydrolysates derived from lignocellulose is challenged by their complex and heterogeneous composition and the presence of inhibitory compounds, such as furan aldehydes. Using microbial consortia where two specialized microbes complement each other could serve as a potential approach to improve the efficiency of lignocellulosic biomass upgrading.ResultsThis study describes the simultaneous inhibitor detoxification and production of lactic acid and wax esters from a synthetic lignocellulosic hydrolysate by a defined coculture of engineered Saccharomyces cerevisiae and Acinetobacter baylyi ADP1. A. baylyi ADP1 showed efficient bioconversion of furan aldehydes present in the hydrolysate, namely furfural and 5-hydroxymethylfurfural, and did not compete for substrates with S. cerevisiae, highlighting its potential as a coculture partner. Furthermore, the remaining carbon sources and byproducts of S. cerevisiae were directed to wax ester production by A. baylyi ADP1. The lactic acid productivity of S. cerevisiae was improved approximately 1.5-fold (to 0.41 ± 0.08 g/L/h) in the coculture with A. baylyi ADP1, compared to a monoculture of S. cerevisiae.ConclusionThe coculture of yeast and bacterium was shown to improve the consumption of lignocellulosic substrates and the productivity of lactic acid from a synthetic lignocellulosic hydrolysate. The high detoxification capacity and the ability to produce high-value products by A. baylyi ADP1 demonstrates the strain to be a potential candidate for coculture to increase production efficiency and economics of S. cerevisiae fermentations.

Digitalization of agriculture in the Republic of Belarus: technological solutions for development

The Republic of Belarus, striving for modern technologies, is actively introducing innovations into the agricultural sector. One of the main advantages of digitalization of agriculture is the opportunity to increase production efficiency and improve product quality. Thanks to the use of modern information technologies, agricultural producers can manage all aspects of their farms, from planning crops to harvesting and crop storage conditions. This allows you to more accurately allocate resources, increase productivity, as well as reduce losses and avoid possible risks.

The concept of an intelligent mobile application with elements of augmented reality and PLM software for value stream mapping

AbstractGrowing demands for variability, reducing losses and increasing production efficiency bring difficult tasks for business management. In order to cope with increasingly demanding tasks, a good knowledge of effective management methods is required, as well as orientation in a wide range of application programs. One of the approaches dealing with reducing losses and streamlining selected processes is the introduction of the Lean philosophy. This philosophy is firmly embedded in the concept of Industry 4.0 and its principles are proving to be highly effective. In the presented contribution, we will focus on the possibilities of reducing losses by implementing selected Lean principles in conjunction with selected program resources and elements of mixed reality. The goal is to create an intelligent mobile application that, based on a simulation model, would enable an in-depth analysis of selected processes from the aspect of material value stream mapping analysis. The model created in this way could serve as a relevant basis for top management in the search for solutions to optimize processes. In the article, we evaluate selected Lean methods, create a workplace simulation model using the PLM simulation tool Tecnomatix Plant Simulation, and the obtained data are presented in an intelligent mobile application based on augmented reality. After the online update, the created application conveys all required relevant information to managers and simplifies their decision-making process.

Reinforcement Learning-Based Multiobjective Evolutionary Algorithm for Mixed-Model Multimanned Assembly Line Balancing Under Uncertain Demand.

In practical assembly enterprises, customization and rush orders lead to an uncertain demand environment. This situation requires managers and researchers to configure an assembly line that increases production efficiency and robustness. Hence, this work addresses cost-oriented mixed-model multimanned assembly line balancing under uncertain demand, and presents a new robust mixed-integer linear programming model to minimize the production and penalty costs simultaneously. In addition, a reinforcement learning-based multiobjective evolutionary algorithm (MOEA) is designed to tackle the problem. The algorithm includes a priority-based solution representation and a new task-worker-sequence decoding that considers robustness processing and idle time reductions. Five crossover and three mutation operators are proposed. The Q -learning-based strategy determines the crossover and mutation operator at each iteration to effectively obtain Pareto sets of solutions. Finally, a time-based probability-adaptive strategy is designed to effectively coordinate the crossover and mutation operators. The experimental study, based on 269 benchmark instances, demonstrates that the proposal outperforms 11 competitive MOEAs and a previous single-objective approach to the problem. The managerial insights from the results as well as the limitations of the algorithm are also highlighted.

Modulation of chicken gut microbiota for enhanced productivity and health: A review.

Microbiota in the digestive tract has become an interesting topic for researchers in recent years. The profile of chicken digestive tract microbiota and its relationship with health and production efficiency have become basic data for modulating the diversity and abundance of the digestive tract microbiota. This article reviews the techniques used to analyze the diversity, role, and function of the gastrointestinal microbiota and the mechanisms by which they are modulated. The gut microbiota plays an important role in animal production, especially during feed digestion and animal health, because it interacts with the host against pathogens. Feed modulation can be a strategy to modulate gut composition and diversity to increase production efficiency by improving growth conditions.

“The Book Which Increases the Human Efficiency”

This article reframes the introduction of Taylorism in early Republican China as the origin point for an enduring social ideal of “scientific management” across modern Chinese society. Previous scholars have argued that Taylorism had a limited impact on Chinese industry before the 1920s and 1930s, but this conclusion overlooks a pervasive intellectual impact. A global phenomenon originating in the United States, Taylorism was not just methods to increase production efficiency. It was also a utopian vision to reorganize society around perfected technocratic hierarchies. Its first Chinese translators all enthusiastically embraced this universal vision, promoting this American “science” as a panacea that would both accelerate China's industrialization and improve its supposedly inefficient public. China's first advocates of scientific management spread these ideas far beyond industry through mainstream publications and urged their universal adoption. While Taylor's methods only shaped a few industrial enterprises before the 1920s, they nonetheless seeded a capacious ideal of a scientifically managed society that remains today.

CONCEPT DESIGN FOR OPTIMIZING MASS PRODUCTION PROCESSES WITH 3D PRINTER IN THE INDUSTRY

This study deals with the conceptual design of three-dimensional (3D) printer technology for process optimization in industrial production. While initially 3D printers were primarily used for rapid prototyping, advancements in technology have transformed them into a new technology for mass production. Within the scope of this study, firstly, investigations were conducted on how Industry 4.0 technologies (internet of things (IoT), smart factories) are utilized on the production line. The first-in, first-out (FIFO) method, which is used in communication between objects (3D printer, industrial robot arm, conveyor belt, and assembly unit), has been elaborated in detail. The aim of this study is to comprehensively address and convey how Industry 4.0 technologies increase production speed and efficiency in mass production processes through the created conceptual design. In the obtained conceptual design, even though the production line has been kept limited, every stage of the production process has been thoroughly explained and examined from start to finish. Within the scope of the study, sample data of the production stages are presented with the sample software called 3D Production and Automation Software (3D MAS), which was developed using the C# programming language on Microsoft Visual Studio Community 2022 IDE. In the next study, efforts can be directed towards expanding the limited production line presented in this work, introducing other Industry 4.0 technologies, and incorporating them into the conceptual design of the production process.

The Impact of Product Development Challenges on Innovation Management of Charcoal Briquettes in Medan (Case Study: Rumah Briket Medan Amplas)

The purpose of this research is to know and analyze the The Impact of Product Development Challenges on Innovation Management of Charcoal Briquettes at the Medan Amplas Briquette House. The research method used is a qualitative method with interviews and literature study as data collection techniques. Based on survey result releved that limited resources and technology, low knowledge and expertise, and limited market access are the main challenges. To address this issue, partnerships with research institutions, employee training, and digital marketing are recommended. Implementation of this strategy is expected to increase production efficiency, competitiveness and business desirability. This research provides guidance for other SMEs and encourages further research into sustainable product innovation.

Hydrogen peroxide production via pH manipulation using Visible-Light photocatalyst (ZnIn2S4) conjugated with Oxygen-Modified black carbon

Hydrogen peroxide (H2O2), a powerful oxidizing agent, plays a critical role in various sectors including bleaching, wastewater treatment, sterilization, chemical manufacturing, healthcare, energy generation, and environmental cleanup. The conventional method for producing H2O2, known as the anthraquinone process, faces challenges due to its economic inefficiencies and significant safety concerns. This has spurred interest in developing safer and more environmental friendly photocatalysts for H2O2 production. These photocatalysts, when dispersed in water and exposed to sunlight, generate H2O2 by extracting oxygen from the air and hydrogen from water. Our research explores the use of zinc indium sulfide (ZnIn2S4), a material that is photoactive under visible light, which accounts for about 43 % of the solar spectrum. Initially, the pH of the solution was not modified, leading to the ionization of Zn and In. However, upon optimizing the experimental conditions, we observed a substantial reduction in particle ionization and an increase in H2O2 yield. Additionally, by integrating black carbon with oxygen functional groups into the ZnIn2S4 matrix, we achieved a 14 % increase in production efficiency compared to traditional methods.

Proactive Manufacturing Strategy for Managing the Multiproduct Production Plan

The case study focuses on a multi-product company in Indonesia that aims to develop a proactive manufacturing strategy to tackle production disruptions caused by process uncertainty. Data from 30 periods are analyzed to evaluate the company's weekly production plan performance, revealing consistent quantity fulfillment but significant discrepancies in the types of products produced compared to the plan. Process uncertainty, especially regarding quality, leads to disruptions such as uneven and inadequate material supplies. Statistical Process Control (SPC) tools, like Pareto analysis, are used to identify priority quality issues, forming the basis for Fault Tree Analysis (FTA) to trace root causes and determine intervention points. Each machine's limited set of valves and pipes poses challenges for thorough cleaning during downtime and quality management outside working hours. Introducing backup valves and pipes per machine can mitigate these issues and improve production efficiency. Companies can implement procurement strategies for pipes and valves to prevent dirty prints in the primary process, ensuring smooth material supply and minimizing disruptions. Although actual production plan achievement hasn't reached 100%, this strategy has the potential to increase product sales by 3.31% by reducing the rejection ratio of dirty prints. Ultimately, proactive procurement of spare pipes and valves is expected to increase production efficiency by 4%, indicating enhanced production schedule stability.

Mobile Robot Detects Pests And Diseases In Palm Oil Nurseries

The palm oil industry is an important economic pillar in various countries, making a significant contribution to global vegetable oil production. Despite its vital role, oil palm growth is often faced with serious challenges such as pest and disease attacks that can threaten crop yields and plant health. Oil palm seeding, as the initial stage in the plant growth cycle, is key in ensuring optimal quality and productivity in the future. The successful application of mobile robot technology in detecting pests and diseases in oil palm nurseries will not only increase production efficiency, but also support the principles of sustainability and wise resource management.

The Bullwhip Effect in Servitized Manufacturers

The shift to a service-oriented economy has driven traditional product-oriented manufacturing firms to integrate various services into their businesses. This study aims to provide empirical evidence on how manufacturers’ service offerings impact demand variability and intrafirm bullwhip effects. Through “bag-of-words” text mining on 10-K filings of U.S.-listed manufacturing firms, we propose a novel measurement to identify annual services offered. We validate the measurement’s statistical and economic significance and verify its consistency with the results obtained using the large language model (i.e., GPT-4). Services are categorized as complementing product sales (e.g., maintenance and repair) or substituting product sales entirely (e.g., machine hours). Utilizing difference-in-difference techniques, we find robust evidence that manufacturers’ service offerings reduce the bullwhip effect in two steps: basic complementing services decrease demand variability, whereas advanced substituting services mitigate intrafirm bullwhip. Moreover, servitization mainly minimizes demand variability through information channels, whereas increased production efficiency decreases intrafirm bullwhip. Our findings contribute to understanding manufacturers’ business model innovations by demonstrating that servitization can smooth demand and mitigate intrafirm bullwhip. This paper was accepted by Karan Girotra, operations management. Funding: This work was supported by the National Natural Science Foundation of China [Grants 71931007, 72091214] and General Research Fund by Hong Kong Research Grants Council [Grant 14505320]. Supplemental Material: The data and the online appendix are available at https://doi.org/10.1287/mnsc.2023.01026 .

Advanced Technologies in Food Processing—Development Perspective

Research into innovative techniques in food technology is developing dynamically. This is indicated by the significant increase in the number of scientific studies in this field. The aim of this work was to provide a comprehensive, in-depth analysis of the available scientific evidence on new techniques used in food that not only increase efficiency but also enable the creation of products with desirable sensory and nutritional characteristics. Research on techniques including cold plasma, high-pressure processing, ultrasound, pulsed electric fields, sous vide, and microwave heating aims to provide innovative methods of food processing, in the context of meeting growing consumer expectations and optimizing production processes in the food industry. Compared to traditional food processing methods, innovative techniques can provide more efficient solutions in the processing of products. Research on alternative non-thermal methods in food technology suggests their possible benefits, including enhancing sensory and nutritional quality, minimizing environmental impact, and increasing production efficiency, which are a significant challenge in the modern food industry. Despite the many benefits, it is worthwhile to continue research to further improve modern food technologies.

Research on Optimization of an Open-Bench Deep-Hole Blasting Parameter Using an Improved Gray Wolf Algorithm

The blasting quality of open-pit mining can be enhanced and the production cost of stope reduced by establishing a mathematical model for step drilling and blasting costs based on stope consumption. By enhancing the Gray Wolf algorithm, the parameters for step drilling and blasting are optimized, resulting in improved effectiveness for step blasting mining, as demonstrated through modeling and calculation. The enhanced Gray Wolf algorithm effectively enhances the blasting performance, reduces production costs, and increases production efficiency. Taking a limestone mine as an example, the optimized drilling and blasting parameters are as follows: hole spacing of 4.62 m, row spacing of 4 m, and explosive consumption rate of 0.23 kg/t; based on these parameters, the stope’s production cost is reduced to CNY 7.7.