Manufacturing Areas Research Articles

Influence of ECM process parameters on SS316 material

Electro-Chemical Machining (ECM) seems to be a hopeful technique in the production area of automobile manufacturing and other productions. In recent years, the demand for stainless steel (SS) micro products and components has evolved significantly in fields such as biotechnology, electronics, optics, medicine and so on. This stainless-steel material is ideal for hygienic environments because it is easily sterilized and corrosion resistant. The process parameters of ECM for stainless steel material are investigated experimentally in this study. The SS-316 alloy was chosen to influence the electrochemical machining process with different electrodes and to investigate process parameters using SEM analysis. The tool material has been changed to investigate the improved quality of ECM process parameters.

A simple Node-RED implementation for digital twins in the area of manufacturing

Interest in digital twins continues to strengthen with technological advancements in Industrial IoT. A digital twin is a virtual representation that models a physical object and effectively provides a two-way interaction with the real system. Digital twin models can be set up to test or analyze industrial applications before deployment thereby improving the efficiency of industries. In this work, a Node-RED implementation for digital twins in the manufacturing sector is developed. Plastic injection molding is the chosen case study for the implementation of this digital twin. Node-RED is a platform that allows developers to quickly build Internet of Things applications using a simple web browser interface. The digital twin uses the Random Forest Classifier algorithm to do predictive maintenance tasks including classification of quality of products. An easy-to-use dashboard is developed to enable the user to interact with the digital twin. Important modules such as communication with the real environment, SMS, and email notifications are successfully implemented in the digital twin. The findings show that it is feasible to build a Node-RED digital twin. The flexibility of Node-RED makes it suitable for building architecture of varying complexity.

Artificial intelligence and its relevance in mechanical engineering from Industry 4.0 perspective

ABSTRACT In the third industrial revolution (IR), mechatronics engineering has emerged, which is the merger of mechanical and electronics engineering along with information technology to an extent. In the current industrial revolution (fourth), the amalgamation of mechanical with Artificial intelligence (AI) has been used to simulate human behaviour in machines. In the earlier decades, the application of AI in mechanical engineering has expedited and the increased volume of related research papers is a proof of this fact. The broad domain of mechanical engineering has a lot of potential for machine learning applications in order to detect errors, minimise rejection, improve product quality, optimise a system, and so on, as it has not been intensely explored although. This article’s goal is to give a structured evaluation of works that employ vision systems and to attract researchers to analyse its potential integration with machine learning (ML) techniques from the industry 4.0 viewpoint. Current trends and research gaps in the area of manufacturing in collaboration with ML are also discussed at appropriate places. A general procedure to carry out research in the field of mechanical engineering is also presented. The results of various studies highlighted in this paper confirm that the implementation of AI in ME has provided an optimum solution to many mechanical problems that improved product quality and minimised the associated cost. Finally, the authors have led a direction to empower researchers in order to explore various areas in mechanical engineering from Industry 4.0 and AI perspective and enable possible topics for future research. The article concludes by providing challenges that may be faced in the coming future about the use of machine learning in mechanical engineering problems.

Electrospinning is a potential way for preparing edible plant protein-based nanofibers with porous surface using safflower seed meal

Food microstructure design has become an important research area in artificial food manufacturing. The fibrous structure is one of the most critical elements since it is the fundamental building blocks constructing the structure of several important food matrices. However, at present, edible fibers at nanoscale are seldomly successfully manufactured due to technical difficulties when only food-grade materials are allowed to be used. In the current study, edible nanofiber consisting of a single component of safflower seed meal protein (SMP) was prepared based on a three-step protocol consisting of electrostatic spinning, protein-cinnamaldehyde cross-linking, and subsequent immersion in the citric acid buffer to remove none-protein components. Addition of pullulan (PUL) to SMP during electrospinning facilitated fibrous structure formation. Results of SEM demonstrated that SMP: PUL = 5:5 with combined ratio 20% (w/v) in water is the upper limit to obtain well-structured composite nanofiber with no addition of Tween 80. In the second step, protein-cinnamaldehyde cross-linking was implemented to stabilize the structure of SMP. In the last step, citric acid buffer with pH4.6 was used to remove pullulan residues and thereafter nanofibers with porous surfaces composed of only SMP were successfully obtained. Our results showed that SMP single-component nanofibers had high thermal stability and good water-holding capacity, and thus suggesting that electrospinning can be a potentially innovative strategy to manufacture food fibrous microstructures especially at nanoscale.

Detection of African Swine Fever Virus in Feed and Feed Mill Environment Following Extended Storage

One way to mitigate risk of feed-based pathogens for swine diets is to quarantine feed ingredients before inclusion in complete diets. Data have been generated evaluating the stability of swine viruses in ingredients, but the stability of African swine fever virus (ASFV) in feed or in a feed manufacturing environment has not been well characterized. Therefore, this study aimed to determine the stability of ASFV DNA in swine feed and on mill surfaces over time. A pilot-scale feed mill was used to manufacture six sequential batches of feed consisting of a batch of ASFV-free feed, followed by a batch inoculated with ASFV (final concentration = 5.6 × 104 TCID50/g), and then four subsequent ASFV-free batches. After each batch, 10 feed samples were aseptically collected in a double “X” pattern. During feed manufacturing, 24 steel coupons were placed on the floor of the manufacturing area and allowed to collect dust during feed manufacturing. Once feed manufacturing was completed, feed samples and steel coupons were stored at room temperature. Three of each were randomly selected from storage on 3, 7, 14, 28, 60, 90, and 180 days after feed manufacturing and analyzed for ASFV DNA. For feed samples, there was evidence of a batch × day interaction ( P = 0.023 ) for the quantification of genomic copies/g of feed, indicating that the amount of ASFV DNA present was impacted by both the batch of feed and days held at room temperature. There were no differences of genomic copies/g in early batches, but quantity of detectable ASFV decreased with increasing storage time. In Batches 4–6, the greatest quantity of ASFV DNA was detected on the day of feed manufacturing. The lowest quantity was detected on Day 7 for Batch 4, Day 60 for Batch 5, and at 28 and 180 days for Batch 6. There was no evidence of ASFV degradation on environmental discs across holding times ( P = 0.433 ). In conclusion, the quarantining of feed may help reduce but not eliminate the presence of ASFV DNA in feed over time. Importantly, ASFV DNA was detectable on feed manufacturing surfaces for at least 180 days with no overt evidence of reduction, highlighting the importance of bioexclusion of ASFV within feed manufacturing facilities and the need for thorough/effective decontamination and other mitigation processes in affected areas.

From Sci-Fi to Reality: The Impact of AI on Automotive Manufacturing and Design

As Artificial Intelligence (AI) continues to advance, it is having a significant impact on the automotive industry, particularly in the areas of manufacturing and design. This paper explores the impact of AI on automotive manufacturing and design, including its influence on autonomous vehicles, supply chain management, predictive maintenance, quality control, and the workforce. It also examines the role of AI in designing sustainable automotive systems, as well as the ethical considerations of its use in the industry. Additionally, the paper considers the impact of popular culture, specifically sci-fi movies and TV shows, on the development and adoption of AI in the automotive industry.

Fueling the future: A comprehensive review of hydrogen energy systems and their challenges

This comprehensive study assesses the current state of the hydrogen energy system and investigates its potential to transform the global energy landscape while addressing important concerns about climate change. While hydrogen energy has numerous advantages, including sustainability and cleanliness, it faces substantial challenges in the areas of storage, manufacturing, distribution, infrastructure, safety, and cost. Scholars, lawmakers, business leaders, and the general public must all work together to address these complex issues. The research emphasizes the significance of breakthrough technology and astute government policies for the successful development and widespread deployment of hydrogen energy systems. It highlights that this revolutionary effort cannot be performed in solitude. Public education and enhanced awareness appear to be significant factors in promoting greater acceptance and use of hydrogen energy. Furthermore, the study identifies critical future research objectives. It underlines the importance of enhancing the efficiency, sustainability, safety, and economic feasibility of hydrogen energy systems. The development of new storage systems, superior infrastructure designs, and seamless integration technologies is vital to achieving the full potential of hydrogen energy. Finally, the research presented here gives a critical assessment of the hydrogen energy situation and outlines a roadmap toward a more sustainable and resilient future. The review's conclusions are significant for policymakers, academics, and stakeholders because they provide critical insights into the opportunities and problems associated with realizing the full potential of hydrogen energy.

Dynamics of India Development Aid to Nigeria in the Post Cold War Era

Following the collapse of the Union of Soviet Socialist Republics (USSR) in 1991, and India pro- market economic reforms of 1991, have affected its relationship with outside world including Nigeria. This paper examines the development aid relations between Nigeria and India after the return of Nigeria to democratic rule from 1999-2007, especially the trade and investment activities of India in Nigeria particularly in area of agriculture, manufacturing, and extractive sector of Nigeria economy. The paper is anchored on dependency and underdevelopment theory to assess actual beneficiary of the development aid relations, and to demonstrates the asymmetric nature of the relationship between Nigeria and India. It has been revealed from the study that after the cold war development aid relations between Nigeria and India has been shifted from idealistic ideology to realistic pro- market economic ideology. It is also noted that, the asymmetric nature of the relationship has hampered the development of Nigeria. This was as a result of unequal trade and investment relations, has India have enormous advantage over Nigeria because of its technological and economic advancement. Therefore, the paper argued that for Nigeria to benefit from the India’s development aid relations, the relationship has to be redesigned to allow for transparency and equal opportunity

ON THE DETERMINATION OF THE SPECIFIC HEAT FLUX VALUE IN A PULSE DETONATION ENGINE’S CHAMBER

Abstract. The development of detonation engines (DE) is one of the most promising areas of rocket and space engine manufacturing. They are more efficient as compared to the liquid rocket engines and are structurally simpler. At the same time, the detonation engine chamber’s structure is subjected to much higher thermal loads. Therefore, at the development stage of the DEs, to create an efficient cooling system for the engine’s chamber, it is necessary to be able to determine the value of thermal energy, which is absorbed by the walls of the DE’s chamber. The goal of this research is to determine the specific heat flux from the detonation products towards the walls of the pulse detonation engine’s (PDE) chamber. The task of the work is to establish the methodology for calculating the values of the specific heat flux transmitted to the walls of the PDE’s chamber. The main tools for solving this problem are the method of mathematical simulation using computational fluid dynamics (CFD), and the method of regression analysis. The main results of this study: the possibility to utilize the well-known Ievlev methodology to determine the convective specific heat flux for the PDE’s chamber was analyzed; it was shown that for the conditions of the PDE’s chamber, the Ievlev methodology calculation results differ significantly from the experimental data, which can be explained by the presence of a clearly pronounced non-stationary nature of the detonation process; it was proven the utilization of the Viegas formula to obtain the values of the convective specific heat flux for the PDE’s chamber gives better results as compared to the known experimental data and the results of the mathematical simulations; it was also demonstrated that the average integral value of the specific heat flux, determined by the described methodology, can be used to calculate the thermal state of the PDE's chamber. Conclusion: a methodology for calculation of the specific heat flux value for the pulse detonation engine's chamber was proposed. The obtained calculation results are in good agreement with the results of mathematical simulations and known experimental data. The described methodology can be used in the design of cooling systems for the pulse detonation engine’s chambers.

Strategy formulation activities with emphasis on strategic management tools and techniques in Slovak companies

The importance and benefits of strategic management in the business sphere are declared in studies worldwide. It represents an extensive area for research. The purpose of this paper is to evaluate the strategy formulation activities as well as the strategic management tools and techniques used by Slovak companies. Data on 365 manufacturing companies were obtained through an online questionnaire during 2020–2021. Selected methods of inductive statistics helped to analyze the data (the Pearson chi-square test and interval estimates for population proportion). The results show that the potential of analyzed strategy formulation activities is not filled in the Slovak companies. Enterprises only perform certain activities, and attention is focused mainly on setting strategic goals. It prevails a small orientation to sustainable development in strategic goals (only 22% of enterprises). The most used strategic management tools and techniques consist of an analysis of company resources, SWOT analysis, and customer satisfaction. From the point of view of the manufacturing area, no significant differences are defined in the use of the tools. The future management directions should include a variety of strategic management tools from the external environment. At the same time, the given tools should be supplemented with newer strategic tools ensuring flexibility and adaptation to dynamically changing conditions. AcknowledgmentWe wish to thank project VEGA: Scientific Grant Agency of the Ministry of Education, Science, Research and Sport of the Slovak Republic (Project No.1/0093/23 Research on the circular economy potential in the Slovak business environment in the production of innovative products based on recycled materials wood – rubber – plastic).

Design and Performance Analysis of a Torsional Soft Actuator Based on Hyperelastic Materials

Conducting research on soft robots is crucial as there are still many problems that need to be resolved in the areas of material selection, structure design and manufacture, and drive control. Soft manipulators, a subset of soft robots, are now a popular area of study for many researchers. In comparison to typical manipulators, soft manipulators feature a high degree of gripping flexibility and a basic morphological structure. They are composed of flexible materials. They have a wide range of potential applications in healthcare, rehabilitation, bionics, and detection, and they can compensate for the drawbacks of rigid manipulators in some use scenarios. A modular soft-body torsional gripping system is developed after a torsional and gripping actuator is conceived and constructed, and its performance examined. The torsion actuator and the grasping actuator can be combined in the system in a modular fashion. With the help of RGB-D vision algorithms, this multi-modular setup makes it possible to combine soft actuators with various twisting degrees and achieve exact gripping. Through pneumatic control, the target object is precisely grasped and rotated at various angles, enabling the rotation of the target object in three dimensions.

A Method for Designing of Hydraulic Actuators Using Digital Hydraulic Pump and Multichamber Cylinder

Abstract Hydraulic actuation systems have a broad range of applications covering almost all areas of manufacturing and production and also the service industry. However, it is usual for systems to have low energy efficiency. In recent decades, due to global environmental concerns, research in the field of digital hydraulics to develop more efficient hydraulic systems has increased. In this paper, an analysis of the possible combinations of chambers in a multichamber cylinder is presented. A mathematical expression is derived to verify the total number of combinations of chambers that it is possible to achieve for a cylinder with four or more chambers and that result in different constant velocities without cavitation occurring. In addition, a digital hydraulic pump is considered a supply unit and, since it has discrete output flow rates, an analytical method to combine the pump with a multichamber cylinder is developed resulting in a total number of cylinder velocities with a required resolution. For application in a positioning system, design guidelines for an actuator using a cylinder with four chambers and a digital hydraulic pump with three fixed displacement units are presented in which an optimization algorithm for the calculation of the cylinder areas and the volumetric displacement of the pumps is applied. The proposed approaches were applied to design a proof-of-concept and the experimental values presented very good accuracy when compared with the results obtained with the model. Closed-loop position control responses show that the system can achieve the required setting time with a smooth movement and steady-state error of around 1 mm.

Facility Layout Planning for Pyrolyzer Production Using Automated Layouts Design Program (ALDEP) Method

One important factor to consider in increasing productivity in a company is the design of the facility layout. PT Hari Mukti Teknik is keen producing pyrolysis machine to contribute to addressing waste issue in Indonesia. Currently, the facility layout at the company is not suitable to produce pyrolizers as it was set up to produce industrial scale washing machines. To improve production efficiency, PT Hari Mukti Teknik needs facility layout that can be optimized for pyrolizers. The purpose of this study is to provide a layout design proposal for the pyrolysis machine manufacturing process to obtain an effective and efficient process. Here, we used ALDEP method to produce layouts based on consideration of the level of relationship between departments. There were 4 alternatives for the manufacturing and production and two alternative layouts for employee and office area. The design for new layout was selected based on the closeness relationship between the departments. An overall facility layout plan that is required for the production of pyrolysis machines is a building area the total of 1045 m² covering manufacturing, production, employee, office and parking space areas.

Pemberdayaan dan Pelatihan Pembuatan Tampon dan Perlengkapan Kedokteran Gigi pada Ibu Rumah Tangga di Kelurahan Makasar, Kecamatan Makasar, Jakarta Timur

Makasar is a sub-district in East Jakarta Municipality, DKI Jakarta Raya Province. Previously, it was called Kampung Makassar. The women's group in Makasar sub-district already has skills in making dental tampons, perforated cloth mat named ‘duk bolong’, and medical head caps. However, their business/sales distribution knowledge needs to be developed so that their creations can be sold widely and then the result can improve the economy of Makasar sub-district resident. Dental tampon makers in the Makasar sub-district also need counseling regarding the importance of cleanliness in the manufacturing area and supporting equipment for sterilizing the tampons’duk bolong’, and medical head caps so that the products have higher value and ready to use for both public and private use. Besides, the training provided counseling and demonstration on how to create interesting promotion through online media. The results of the counseling are very good and there is an increase in the skills and knowledge of the women in the Makassar sub-district in product manufacture and product marketing.

Sources and health risk assessment of water-soluble and water-insoluble metals in road and foliar dust in Xi'an, Northwest China

Road dust pollution is still an important environmental problem in the cities of northwest China. To better understand the risk exposure and sources of unhealthy metals in road dust and foliar dust, the dust samples were collected in Xi'an city, Northwest China. The sampling period was during December 2019 and 53 metals in the dust were analyzed using Inductive Coupled Plasma Emission Spectrometer (ICPA-RQ). Compared to road dust, most metals are found in relatively higher concentrations in foliar dust, especially water-soluble metals, with Mn being 3710 times more abundant in foliar dust. However, the regional characteristics of road dust are more pronounced, i.e., the concentrations of Co and Ni are six times higher in industrial manufacturing areas than in residential areas. The results of the non-negative matrix factorization and principal component analysis source analyses demonstrate this difference, the dust in Xi'an is mainly from transportation (63 %) and natural sources (35 %). From the emission characteristics of the traffic source dust, brake wear is the main cause of traffic source, accounting for 43 %. However, the metal sources in each principal component of foliar dust show a more mixed state, which is consistent with the results of regional characterization. The health risk evaluation shows that traffic sources are the main risk source and contribute 67 % to the total risk. Among them, Pb from tire wear is the main contribution to the total non-carcinogenic risk for children, which is close to the risk threshold. In addition, Cr and Mn are also worthy of attention. The above results all emphasize the contribution of traffic emissions, especially the non-tailpipe emission component, to dust emissions and health risks. Therefore, controlling vehicle wear and tear and exhaust emissions should be the main way to improve air quality, such as traffic control and improvement of vehicle component materials.

A self-learning interior search algorithm based on reinforcement learning for energy-aware job shop scheduling problem with outsourcing option

Energy-aware scheduling has been viewed as a feasible way to reduce energy consumption during the production process. Recently, energy-aware job shop scheduling problems (EAJSPs) have received wide attention in the manufacturing area. However, the majority of previous literature about EAJSPs supposed that all jobs are fabricated in the in-house workshop, while the outsourcing of jobs to some available subcontractors is neglected. To get close to practical production, the outsourcing and scheduling are simultaneously determined in an energy-aware job shop problem with outsourcing option (EAJSP-OO). To formulate the considered problem, a novel mathematical model is constructed to minimize the sum of completion time cost, outsourcing cost and energy consumption cost. Considering the strong complexity, a self-learning interior search algorithm (SLISA) is developed based on reinforcement learning. In the SLISA, a new Q-learning algorithm is embedded to dynamically select search strategies to prevent blind search in the iteration process. Extensive experiments are carried out to evaluate the performance of the proposed algorithm. Simulation results indicate that the SLISA is superior to the compared existing algorithms in more than 50% of the instances of the considered EAFJSP-OO problem.

Survey and Tutorial on Hybrid Human-Artificial Intelligence

The growing computing power, easy acquisition of large-scale data, and constantly improved algorithms have led to a new wave of artificial intelligence (AI) applications, which change the ways we live, manufacture, and do business. Along with this development, a rising concern is the relationship between AI and human intelligence, namely, whether AI systems may one day overtake, manipulate, or replace humans. In this paper, we introduce a novel concept named hybrid human-artificial intelligence (H-AI), which fuses human abilities and AI capabilities into a unified entity. It presents a challenging yet promising research direction that prompts secure and trusted AI innovations while keeping humans in the loop for effective control. We scientifically define the concept of H-AI and propose an evolution road map for the development of AI toward H-AI. We then examine the key underpinning techniques of H-AI, such as user profile modeling, cognitive computing, and human-in-the-loop machine learning. Afterward, we discuss H-Al's potential applications in the area of smart homes, intelligent medicine, smart transportation, and smart manufacturing. Finally, we conduct a critical analysis of current challenges and open gaps in H-AI, upon which we elaborate on future research issues and directions.

Exact methods for the Oven Scheduling Problem

The Oven Scheduling Problem (OSP) is a new parallel batch scheduling problem that arises in the area of electronic component manufacturing. Jobs need to be scheduled to one of several ovens and may be processed simultaneously in one batch if they have compatible requirements. The scheduling of jobs must respect several constraints concerning eligibility and availability of ovens, release dates of jobs, setup times between batches as well as oven capacities. Running the ovens is highly energy-intensive and thus the main objective, besides finishing jobs on time, is to minimize the cumulative batch processing time across all ovens. This objective distinguishes the OSP from other batch processing problems which typically minimize objectives related to makespan, tardiness or lateness. We propose to solve this NP-hard scheduling problem using exact techniques and present two different modelling approaches, one based on batch positions and another on representative jobs for batches. These models are formulated as constraint programming (CP) and integer linear programming (ILP) models and implemented both in the solver-independent modeling language MiniZinc and using interval variables in CP Optimizer. An extensive experimental evaluation of our solution methods is performed on a diverse set of problem instances. We evaluate the performance of several state-of-the-art solvers on the different models and on three variants of the objective function that reflect different real-life scenarios. We show that our models can find feasible solutions for instances of realistic size, many of those being provably optimal or nearly optimal solutions.

Maintaining Warp Speed: Policy Requirements for a Just-in-Time, Capability-Based, Scalable Medical Countermeasure Research and Development Enterprise.

Maintaining Warp Speed: Policy Requirements for a Just-in-Time, Capability-Based, Scalable Medical Countermeasure Research and Development Enterprise.

Preface

To adapt to the changing international and domestic circumstance in the new era, the 2022 2nd International Symposium on Artificial Intelligence and Intelligent Manufacturing (AIIM 2022) was held in Nanjing, China during December 2nd to 4th, 2022 (virtual form). Everyone interested in the fields related to Artificial Intelligence and Intelligent Manufacturing were welcomed to join the online conference and give comments and raise questions to the speeches and presentations.The 2022 2nd International Symposium on Artificial Intelligence and Intelligent Manufacturing is an international academic conference. It built an international platform for the communication and academic exchange among all the participants from related fields, providing a good opportunity for all the participants to share research results, and build global partnership for potential collaboration.The online conference consisted of Keynote Speeches and Oral Presentations, attracting about 50 individuals from all over the world. We have invited three sophisticated professors to perform keynote speeches. Among them, Assoc. Prof. He Chen from Hebei University of Technology, China delivered a wonderful keynote speech on Control Research for Underactuated Cranes with State Constraints. Due to the underactuated properties, less control inputs are used to dominate more degrees of freedom for cranes, which increases the control difficulty. And still the working environment for cranes may be complex, various state constraints should be considered for the control design of cranes to ensure safety. Considering these factors, in this presentation, he proposed three different kinds of control methods with state constraints to deal with different crane transportation issues. He also extended the proposed method to solve the state constraint control problem for a class of underactuated systems. All keynote speakers made brilliant speeches and shared unique professional experience and insights, triggering heated discussion.AIIM 2022 received a great many submissions in the areas of Artificial Intelligence and Intelligent Manufacturing. Each submission was reviewed by at least two expert reviewers and the committee picked out some excellent papers that are included in the proceedings, covering but not limited to the following topics: Artificial Intelligence, Computer Vision, Intelligent Manufacturing, Industrial Design and Manufacturing, etc.On behalf of the Conference Organizing Committee, we would like to thank the Technical Program Committee members and external reviewers for their hard work in reviewing and selecting papers. And we would like to acknowledge all of those who supported AIIM 2022. Particularly, our special thanks go to the Journal of Physics: Conference Series. We deeply appreciate their efforts in making the conference successful.The Committee of AIIM 2022List of Committee Member is available in this pdf.