Mechanical Manufacturing Industry Research Articles

The Application of Artificial Intelligence Technology in Mechanical Manufacturing and Automation

In order to achieve intelligent production and quality control, improve production efficiency and accuracy, the author proposes an application method of artificial intelligence technology in mechanical manufacturing and automation. The author aims to explore the specific application of artificial intelligence technology in the mechanical manufacturing industry and summarize the main advantages of automation technology. By analyzing these advantages, the aim is to provide targeted recommendations for future technological development. Meanwhile, the author aims to provide theoretical support for promoting the application of modern artificial intelligence technology and automation technology in the field of mechanical manufacturing. In the manufacturing process, intelligent production and quality control can be achieved, improving production efficiency and accuracy; In the field of automation, artificial intelligence technology can achieve intelligent control systems and autonomous decision-making, improving the flexibility and adaptability of production lines. Overall, the application of artificial intelligence technology has brought revolutionary changes to mechanical manufacturing, promoting the upgrading and development of the industry.

Multi-objective modeling and evaluation for energy saving and high efficiency production oriented multidirectional turning considering energy, efficiency, economy and quality

To promote energy saving, high efficiency and quality production in the mechanical manufacturing industry, a large number of studies have been conducted on modelling and evaluation. However, most of the approaches have focused on single objective modelling, evaluation and conventional machining method like unidirectional turning (UDT). This paper presents a multi-objective modelling and evaluation method for energy, efficiency, economy and quality using a new process of forward-and-reverse multidirectional turning (MDT). Firstly, the multi-objective influential factors of cutting parameters for energy consumption, cutting time, production cost and surface roughness of MDT are analyzed to establish the corresponding models, respectively. Then taking the energy consumption, cutting time, production cost and surface roughness as the objectives, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is applied for the multi-objective evaluation through different processes. Finally, the case study shows the practicability of the MDT method and evaluation method for energy optimization and energy conservation.

Multi-objective optimisation for energy saving and high efficiency production oriented multidirectional turning based on improved fireworks algorithm considering energy, efficiency and quality

To promote energy saving, high efficiency and quality production in mechanical manufacturing industry, a large number of studies have been conducted on parameters optimisation, especially for turning. However, most of the approaches have focused on single objective model and unidirectional turning (UDT). This paper presents a multi-objective parameter optimisation method for energy consumption, cutting time and surface roughness using new process of forward-and-reverse multidirectional turning (MDT). Firstly, the composition characteristics of cutting parameters for energy consumption, cutting time and surface roughness of MDT are analyzed to establish the corresponding models through nonlinear regression fitting, respectively. Then taking the minimum energy consumption, cutting time and surface roughness as the optimisation objectives, the improved fireworks algorithm can generate nearly 100 groups of optimal solutions. The most suitable processing parameters solution needs to be selected according to different machining requirements. In application scenarios, most relative errors of the models are within 10%. Comparing the machining performance of MDT and UDT under the same cutting parameters, the processing efficiency is increased by 25.97% and energy consumption is reduced by 12.38%, using the MDT. This study provides a multi-objective optimisation approach and models for MDT to reduce energy consumption, improve production efficiency and quality.

Simultaneous sensing of strain and temperature based on the inline-MZI embedded point-shaped taper structure with low crosstalk.

An embedded spherical dot taper structure (EDT) based on the MZI principle is proposed in this paper, which is mainly fabricated by using two special arc discharges in the preparation process. The proposed structure involves two specialized arc discharge techniques. First, an oversaturated discharge fusion process creates a micro-arc spherical area on the fiber end face to form the first link type. Second, an unsaturated discharge-pulling taper fusion joint creates a local micro-extrusion operation on this micro-arc fiber end face to form the second link. The thermal stress from instantaneous discharge causes a reverse spherical expansion zone to form in the end face structure, similar to the micromachining of long-period fiber gratings that use local CO2 laser etching to create modulated zones. The study involves a mathematical and theoretical analysis of how geometric parameters in the spherical modulation zone impact the structure's characteristic spectrum. The research demonstrates the potential for this structure to function as a light-intensity modulated strain sensor device through both theoretical and experimental means. As per the experimental findings, the optimized structure displays a high level of strain sensing sensitivity at 0.03 dB/µε and temperature sensing sensitivity of 73 pm/°C (20°C-75°C) and 169 pm/°C (75°C-120°C). Additionally, it possesses excellent cross-sensitivity at only ∼0.0015 µε/°C. Therefore, this sensor presents a favorable option for strain and temperature synchronization sensing and monitoring components, and exhibits notable application prospects in precision engineering, which encompasses mechanical manufacturing, the power and electrical industry, healthcare domain, and certain specialized areas of small-scale precision engineering.

The Human Resource Management Practices for the Implementation of TQM in Indian Manufacturing Industries

Purpose: Examine the association between human resource management(HRM) practices and the total quality management (TQM) practices in the meppchanical manufacturing industries. Design/Methodology/Approach: Data and information were gathered using a survey instrument. Data were collected from the managerial level employees working in the HR, quality and production departments. Collected data and information were analyzed using descriptive statistics, factor analysis and structural equation modelling. Findings: Human resource management practices are associated with total quality management practices. The result of the study also reveals that Functional Leadership (FL), Positive Organizational Scholarship (POS), Employee Involvement (EI), Empowerment (EMP) and Employee Training (ET) are the predominant factors of human resource management. At the same time, Benchmarking (BEN), Customer Satisfaction (CS), Top Management Commitment (TMC) and Supplier Relations (SR) are the critical success factors of TQM practices. “Functional Leadership” has the most significant impact on Benchmarking. Research limitations/implications: The empirical research was on mechanical manufacturing industries in India only. Further, the study can be extended to other sectors to gather relevant TQM and HRM associations. Practical implications: Successful implementation of HRM practices enhances employees' motivation level; this will significantly help to implement the organization's TQM practices. Overall implementation of HRM and TQM practices will improve employee satisfaction and customer satisfaction level and continuous improvement. Originality/value: The research tender imminent into associations between HRM and TQM practices focusing on Indian manufacturing organizations. This conceptual framework is a valuable reference for future research.

CAD/CAM Based Aided Design of Mechanical Product Shape

To meet the requirements of the mechanical manufacturing industry for improving the machining quality of parts, and enhance the machining accuracy and the rationality of part design, a CAD/CAM integrated feature modeling aided system is introduced. According to the characteristics of mechanical products, we propose an integrated CAD set editing framework. On this basis, an optimized incremental feature recognition method is adopted to correlate design features with manufacturing features Then, the digital model of the original model is re-established in Pro/E system, and the strength and stiffness of the molded part of the case are analyzed by comprehensively applying ANSYS software and RP technology, which proves the effectiveness and feasibility of the scheme in this paper.

Optimization techniques for energy efficiency in machining processes-a review.

Metal working process is one of the main activities in mechanical manufacturing industry; it is considered as a major consumer of energy and natural resources. In material removal process, the selection of cutting parameters and cooling or cutting liquid is necessary to save energy and achieve energy efficiency as well as sustainability. During the last two decades, the number of publications in this field has rapidly increased and has shown the importance of this research area. This review paper identifies and reviews in detail a total of 166 scientific studies which exhibit original contributions to the field and address multiple energy efficiency challenges. The recently developed models of energy consumption and different materials used in the machining process are presented. Therefore, this study describes various techniques for modeling and optimizing machining operations such as turning, milling, and drilling. Modeling techniques, experimental methods, multi-objective and single-objective optimization methods, and hybrid techniques optimization are presented in a detailed manner compared to previous review papers where only energy models are discussed. It can help practitioners and researchers to select the most appropriate approach for the desired experience and to highlight the progress of these methods in terms of machining energy efficiency. Additionally, this paper provides a review of different cutting fluids adopted in machining processes. This paper assists researchers and manufacturers in making advantageous technical decisions that have substantial economics in terms of energy saving.

Applications of Artificial Intelligence in Mechanical Engineering

Artificial intelligence (AI) technology, as one of the most sophisticated science and technology in today's world, is increasingly being used to production and life, particularly in the manufacturing business. it demonstrates how artificial intelligence technology is used in mechanical manufacturing, namely in defect detection, quality inspection, enhancing workplace safety, and other areas. Artificial intelligence technology is becoming increasingly important in people's lives as it becomes more widely used in people's daily lives, such as the widespread use of smart dishwashers and smart sweepers, which are the products of the fusion of artificial intelligence and the mechanical manufacturing industry. Indeed, artificial intelligence technology has been widely utilized in the mechanical manufacturing business, which not only ensures production precision, but also enhances job productivity and workplace safety. The rise of artificial intelligence has caused significant changes in the manufacturing industry as a whole. Without exception, the manufacturing industry must rely on AI technology to accomplish automation and intelligent development, as well as to improve productivity. Using artificial intelligence to categorize mechanical components, we may propose parts from a based solely on an image or CAD model. To find a necessary component in a machines we must currently browse through a catalogue and be able to discern which part you want based on the available possibilities and your understanding of the catalogue. There are serial numbers to memorize since a single digit or character change might indicate a different sort of part. The algorithm will choose which sections are the best and will significantly facilitate our search.

Forward-and-reverse multidirectional turning: A novel material removal approach for improving energy efficiency, processing efficiency and quality

To address the issue of high energy consumption and low utilization rate in conventional turning, a concept of forward-and-reverse multidirectional turning (MDT) and the MDT approach are proposed to reduce energy consumption in idling and to improve processing efficiency and surface quality. The material removal performance of the MDT from aspects of energy consumption, processing efficiency, chip morphology and surface quality is discussed to understand its features and advantages compared with unidirectional turning (UDT). In three application scenarios, the processing efficiency is increased by 6.40%, 8.45%, and 7.76%, and energy consumption is reduced by 10.88%, 7.25%, and 9.52%, using the MDT, respectively. Additionally, the MDT has better control ability of the chip removal, benefitting for improving the processing stability. The surface quality of the workpiece processed by the MDT is generally better than that by UDT. This study provides a novel high performance processing approach for the machining,which contributes to promoting the efficient and high-quality development of mechanical manufacturing industry.

Brief Discussion on the Application of Mechanical Automation Technology in Mechanical Manufacturing Industry

Brief Discussion on the Application of Mechanical Automation Technology in Mechanical Manufacturing Industry

High-precision and long-range measurement of micro-gear starting torque.

The ability to measure micro-starting torque is pivotal for micromechanical equipment, which has wide usage in mechanical manufacturing, electrical, electronic, and other industries. However, the measurement range of existing methods is about N⋅m or mN⋅m. There is not much research on the measurement of micro-torque starting in the µN⋅m. In this paper, a novel micro-gear starting torque measurement system, to the best of our knowledge, is proposed based on an optical lever with a long range from 1 to 10µN⋅m. The system device consists of the optical lever, cantilever, and position sensitive device. A micro-gear was used to assess the performance of the proposed method. The standard deviation of the measured starting torque is 1.2µN⋅m. The external factors that can contribute to the uncertainty of the measurement system, such as force measurement, arm of force, and repeatability, have been analyzed and quantified. The relative combined uncertainty is estimated at 3.0%, approximately.

Metal Particles Velocity Measurement Based on Capacitance Sensor With Double Triangular-Shaped Electrodes

How to measure the flow velocity of metal particles flowing in the pipeline is a urgent problem in mechanical manufacturing industry due to the complex flow state of metal particles. A novel capacitance sensor with double triangular-shaped electrodes (CSDTE) is presented for measuring the average velocity of metal particles flowing within a small-diameter pipeline. Firstly, the operating principle of CSDTE for measuring metal particles is theoretically deduced. Then the 3D simulation model of CSDTE is built by COMSOL software, and its axial sensitivity distribution is analyzed. On this basis, a quantitative mathematical relationship for velocity measurement is derived by analyzing spatial filtering effect of CSDTE. Finally, a CSDTE-based metal particles velocity measurement system is further developed and a gravity-fed particle flow experimental rig is designed to verify the measurement method. Experimental results indicate that the measurement method is feasible, and its repeatability error is less than 7% over the range of 2.44-5.34 m/s.

Energy saving and high efficiency production oriented forward-and-reverse multidirectional turning: Energy modeling and application

The energy modeling has been recognized as an effective analytical methodology and management tool that helps to predict the energy consumption and to manage the efficiency and performance of energy utilization. With a wide distribution and large amount of energy consumption at a low efficiency, the mechanical manufacturing industry has considerable energy saving potential. In this study, a new method of energy conservation and high efficiency production oriented multidirectional turning is proposed to overcome the performance deficiencies of traditional turning in the mechanical manufacturing industry. Based on energy and production performance analysis, the energy consumption model of the forward-and-reverse multidirectional turning is established through the process stage-oriented modeling method. Besides, the case study indicates the high (more than 97%) accuracy of the proposed energy consumption model for forward-and-reverse multidirectional turning. This study contributes to a new production method and energy models to reduce energy consumption and improve production efficiency.

Quality management system in the supply chain of the metal mechanical manufacturing industry

Successful supply chains manage product flows, information and funds to provide a high level of product availability to the customer. The fundamental challenge today is for supply chains to achieve coordination despite multiple ownership and increasing product variety. The objective then is to coordinate business processes from manufacturers, suppliers, transportation, warehouses, distributors, and partners to the customer in such a way that lower costs, shorter production times and product and service quality adapted to customer requirements are achieved. In the present work, a system is created that evaluates the behavior of the supply chain based on quality. To carry it out, focus groups and exploratory factor analysis with varimax rotation are used to compile the main components of quality management in the SCQM supply chain and the set of dependent variables associated with the determining factors. The results show the most valuable key factors and this is an instrument that allows their evaluation. In the development of the research, the review of impact literature is carried out, methods, techniques and tools such as interviews, document review, work with experts, brainstorming, descriptive analysis and exploratory factor analysis, diagrams or control graphs are used.

Design of a Lifecycle-Oriented Environmental and Economic Indicators Framework for the Mechanical Manufacturing Industry

As a result of the worldwide depletion of natural resources, increased energy use, and environmental, economic, and social imbalance, organizations are working to identify the proper strategies supporting the continuous reduction of their impacts. While this trend is fundamentally agreed upon in the literature, several manufacturing industries still fail to identify which elements most influence their contributions to the impact of sustainability and how to easily manage the calculation of these effects within a manufacturing system. The purpose of this article is to incorporate sustainability practices into manufacturing by developing a set of key performance indicators (KPIs) for assessing and improving environmental and economic management practices at the corporate and production level. The definition of the framework began with in-depth research of the leading indicators and framework types in the literature, integrating the most exploited industrial standards to make them easily acceptable in the industrial domain. Then, to provide a broad view of company behavior, the framework has been designed to take either an inventory and impact point of view, thus providing indicators for the online monitoring of the company operations, or assessing their impacts in an LCA-LCC perspective. In selecting the indicators and the definition of the framework structure, five industrial cases covering different business sectors were involved in identifying the most critical indicators in terms of calculability and defining a structure that would allow for their application in various business situations. Therefore, the defined framework has been validated at a conceptual level, thus laying the basis for future quantitative validation. Twenty key performance indicators (KPIs) for assessing the sustainability of manufacturing firms have been created based on the 163 indicators studied.

Study and Design of Arduino Based CNC Laser Cutting Machine

For precise job manufacturing, system should possess good dimensional accuracy and surface finish. In applications like drilling, punching, marking, boring, tapping work piece is positioned firstly and then cutting tool performs its action while motion axes are kept stationary. In traditional approach for such applications, manufacturer uses highly expensive CNC machine for programming job cycle and executing the same. Big scale manufacturer can afford such highly expensive machines but for small scale mechanical job manufacturing industry we have to think of low-cost solution that can deliver high class output. In this project we are trying to propose low-cost design which gives similar functionality as that of high-cost CNC machine. By applying this machine in industry, it can acquire the multi generation brief time. In order to perform some operation which requires continuous cutting over a pre-defined curve, CNC machines are used as the traditional machines in the industry. Installation of a CNC machine requires a high financial investment and a skilled labour to perform the different operations on the machine. Apart from that the maintenance cost of such machine are also high. In small scale industries where the operations are performed on small job pieces, the installation of such high-cost CNC machine is very difficult; hence this project work is taken up in which a low-cost CNC laser cutting machine is designed using the Arduino. This CNC laser cutting machine will be quite useful for small scale industries where the job size is not very large. Also, the machine does not require a highly skilled labour to perform operations.

Study on Mechanical Properties of Lost Foam Pattern in Machining

Lost foam casting has special requirements on the process performance of molding machinery, and the processing technology of Lost foam casting pattern is one of the core and key technologies of Lost foam casting. The research status of lost foam pattern and the safety problems existing in the process of lost foam casting were analyzed. The mechanical properties of lost foam pattern and its mechanical property model were studied, which provided theoretical support for the research of numerical control processing and safe casting of lost foam pattern. The development of Lost foam casting pattern NC processing technology is conducive to the use of information technology, digital technology to enhance the technological progress of traditional industries, promote the clean production of Lost foam casting, realize energy saving and emission reduction, and promote the rapid development of mechanical equipment manufacturing industry.

TRANSPARENCY OF DESIGN AUTOMATION SYSTEMS USING VISUAL PROGRAMMING – WITHIN THE MECHANICAL MANUFACTURING INDUSTRY

AbstractOne challenge with design automation is system transparency with adjustable granularity because of the many different forms of representation from multiple disciplines. Previous research has focused on visualization through the generation of graphs, packaging into electronic books, and model highlighting. The research presented in this paper focuses instead on a visual programming approach, commonly applied in the building industry, where design assets and external references are wrapped into visual components and managed on a canvas with information input/output relations displayed. This entails additional documentation efforts, but the visualization is arguably more useful as groups and levels of granularity are adjusted by the engineers themselves as a part of the development work. To explore visual programming and its potential benefits as a way of enabling transparency with adjustable granularity of DA systems within mechanical manufacturing industry, an existing textual design automation system was transformed into a visual one using Grasshopper® (a visual programming environment) and discussed with respect to DA system transparency, feature-based CAD, and DA system development.

An integrated contract manufacturer selection and product quality optimization methodology for the mechanical manufacturing industry

Outsourcing is a crucial strategy of the mechanical manufacturing industry. When outsourcing, it is necessary for companies to carefully inspect the performance of contract manufacturers (CMs) to ensure high-quality products and satisfactory services. This study presents an integrated methodology for the quality performance assessment and optimization of products with multiple quality characteristics for CM selection in the mechanical manufacturing industry. First, we present a novel process capability analysis chart (PCAC) using the 100(1–α)% upper confidence limits of Cpmh, Cpuh, and Cplh to gauge the process capabilities of products with multiple quality characteristics and reduce the influence of sampling errors. Second, we apply Pareto optimality to reexamine eligible CMs under the objectives of maximizing performance in individual quality characteristics and minimizing variance in overall performance. A feedback mechanism is included to advise ineligible CMs on means of improvement. Finally, we present a case study to demonstrate the feasibility and effectiveness of the proposed methodology.

Structural equation modeling of E-supplier selection criteria in mechanical manufacturing industries

In today's world of globalization and intense technical competence, the relationship between the mechanical manufacturers and the e-suppliers has turned from antagonist to cooperative. The key factor that maintains such relationships depends on the selection criteria that the manufacturers adopt. This present study selects mechanical manufacturing industries as research subjects to explore the critical e-supplier selection criteria and relationships among these criteria with previous studies' aid. The study will apply Structural equation modeling (SEM) to verify the critical criteria derived and evaluate each key factor's impact based on the modeling results. The study also provides a systematic appraisal of the published literature in Web of Science (WoS)/Scopus databases for the period 1995–2020 for selection criteria and 2005–2020 for selection criteria methods. The analyses extract 52 selection criteria and four significant categories of selection methods. The goodness-of-fit indices validate structural equation model consisting of forty-four criteria divided into eight factors representing the overall e-supplier selection problem to the extent of 94%. Finally, Regression analysis provides the ranks and priority weights of selection criteria. The cost (23.2%) has emerged as the most significant criterion, followed by quality (14.1%) and delivery (12.5%), whereas infrastructure and environment concern (4.5%) ranks at the lowest, followed by management systems (7%). The results of the hypotheses testing uncovered that 14 hypotheses support the model. The research findings may help organizations gain a thorough and better understanding of the selection criterion concepts to enhance their effectiveness, triumph, and competitiveness. The results show that applying a structured decision-making technique is vital, especially under complex conditions that include qualitative and quantitative criteria.