Leveraging Robust Artificial Intelligence for Mechatronic Product Development—A Literature Review

Mechatronic product development is a complex and multidisciplinary field that encompasses various domains, including, among others, mechanical engineering, electrical engineering, control theory and software engineering. The integration of artificial intelligence technologies is revolutionizing this domain, offering opportunities to enhance design processes, optimize performance, and leverage vast amounts of knowledge. However, human expertise remains essential in contextualizing information, considering trade-offs, and ensuring ethical and societal implications are taken into account. This paper therefore explores the existing literature regarding the application of artificial intelligence as a comprehensive database, decision support system, and modeling tool in mechatronic product development. It analyzes the benefits of artificial intelligence in enabling domain linking, replacing human expert knowledge, improving prediction quality, and enhancing intelligent control systems. For this purpose, a consideration of the V-cycle takes place, a standard in mechatronic product development. Along this, an initial assessment of the AI potential is shown and important categories of AI support are formed. This is followed by an examination of the literature with regard to these aspects. As a result, the integration of artificial intelligence in mechatronic product development opens new possibilities and transforms the way innovative mechatronic systems are conceived, designed, and deployed. However, the approaches are only taking place selectively, and a holistic view of the development processes and the potential for robust and context-sensitive artificial intelligence along them is still needed.

Application of Deep Learning to Production Forecasting in Intelligent Agricultural Product Supply Chain

Production prediction is an important factor influencing the realization of an intelligent agricultural supply chain.In an Internet of Things(IoT)environment,accurate yield prediction is one of the prerequisites for achieving an efficient response in an intelligent agricultural supply chain.As an example,this study applied a conventional prediction method and deep learning prediction model to predict the yield of a characteristic regional fruit(the Shatian pomelo)in a comparative study.The root means square error(RMSE)values of regression analysis,exponential smoothing,grey prediction,grey neural network,support vector regression(SVR),and long short-term memory(LSTM)neural network methods were 53.715,6.707,18.440,1.580,and 1.436,respectively.Among these,the mean square error(MSE)values of the grey neural network,SVR,and LSTM neural network methods were 2.4979,31.652,and 2.0618,respectively;and theirRvalues were 0.99905,0.94,and 0.94501,respectively.The results demonstrated that the RMSE of the deep learning model is generally lower than that of a traditional prediction model,and the prediction results are more accurate.The prediction performance of the grey neural network was shown to be superior to that of SVR,and LSTM neural network,based on the comparison of parameters.

Popular Science Animation for the Future Intelligent Agricultural Ecology of Agricultural Products Innovation Design and Promotion

The form of agricultural products promotion is also constantly updated with the continuous development of science and technology in recent years.Intelligent agriculture gradually leads the scientific and technological process of agricultural products planting,production,promotion and other fields,making agricultural production more efficient and controllable.The use of popular science animation in the innovative design and promotion of agricultural products will help to drive the agricultural economy,conform to the current new situation,and improve the competitiveness of agricultural products with the help of scientific and technological strength and innovation consciousness in this environment.

Product quality prediction based on RBF optimized by firefly algorithm

With the development of information technology,a large number of product quality data in the entire manufacturing process is accumulated,but it is not explored and used effectively.The traditional product quality prediction models have many disadvantages,such as high complexity and low accuracy.To overcome the above problems,we propose an optimized data equalization method to pre-process dataset and design a simple but effective product quality prediction model:radial basis function model optimized by the firefly algorithm with Levy flight mechanism(RBFFALM).First,the new data equalization method is introduced to pre-process the dataset,which reduces the dimension of the data,removes redundant features,and improves the data distribution.Then the RBFFALFM is used to predict product quality.Comprehensive expe riments conducted on real-world product quality datasets validate that the new model RBFFALFM combining with the new data pre-processing method outperforms other previous me thods on predicting product quality.

An intelligent system for calculating the scale of rational,enlarged production of an underground non-ferrous metal mine

The enlarged production scale of underground non-ferrous metal mines is affected by many uncertain factors difficult to describe mathematically with any level of accuracy.The problem can be solved by a synthesis of artificial intelligence.Based on the analysis of the major factors affecting the scale of enlarged production,we first interpreted in detail the design principles and structure of the intelligent system.Secondly,we introduced an ANN subsystem.In order to ensure technological and scale efficien- cies of the training samples for ANN,we filtrated the samples with a DEA method.Finally,we trained the intelligent system,which was proved to be very efficient.

Modeling of Agile Intelligent Manufacturing-oriented Production Scheduling System

Agile intelligent manufacturing is one of the new manufacturing paradigms that adapt to the fierce globalizing market competition and meet the survival needs of the enterprises, in which the management and control of the production system have surpassed the scope of individual enterprise and embodied some new features including complexity, dynamicity, distributivity, and compatibility. The agile intelligent manufacturing paradigm calls for a production scheduling system that can support the cooperation among various production sectors, the distribution of various resources to achieve rational organization, scheduling and management of production activities. This paper uses multi-agents technology to build an agile intelligent manufacturing-oriented production scheduling system. Using the hybrid modeling method, the resources and functions of production system are encapsulated, and the agent-based production system model is established. A production scheduling-oriented multi-agents architecture is constructed and a multi-agents reference model is given in this paper.

Intelligent production optimization method for a low pressure and low productivity shale gas well

Shale gas wells frequently suffer from liquid loading and insufficient formation pressure in the late stage of production.To address this issue,an intelligent production optimization method for low pressure and low productivity shale gas well is proposed.Based on the artificial intelligence algorithms,this method realizes automatic production and monitoring of gas well.The method can forecast the production performance of a single well by using the long short-term memory neural network and then guide gas well production accordingly,to fulfill liquid loading warning and automatic intermittent production.Combined with adjustable nozzle,the method can keep production and pressure of gas wells stable automatically,extend normal production time of shale gas wells,enhance automatic level of well sites,and reach the goal of refined production management by making production regime for each well.Field tests show that wells with production regime optimized by this method increased 15%in estimated ultimate reserve(EUR).Compared with the development mode of drainage after depletion recovery,this method is more economical and can increase and stabilize production effectively,so it has a bright application prospect.

Intelligent MSW Biocell Approach for Efficient Methane Production

The aim of this research is to provide approach to enhance methane production and to convert CO2 released into methane via anaerobic degradation. Despite CH4 has more global warming potential than CO2 but it is less available in the environment and it has fuel value. This research suggests approach that methane is being stimulated and carbon dioxide is being converted to methane. The methane enhancement herein is achieved via technical and intelligent processes. The technical processes entail leachate and carbon dioxide recirculation. The recirculated leachate is controlled via fuzzy intelligent system that acquires values of abiotic factors such as C:N:P, pH, temperature, and moisture content, and then these values are introduced to trained fuzzy system to decide the value of methane production quality. The fuzzy logic proceeds in systematic sequence as input, inference through rules, and output. If the fuzzy logic output decision indicates bad production, then the value of aboitic factors are dynamically altered with optimized combination of values. Carbon dioxide is being re-circulated in order to convert it biologically to methane by hydrogenotrophic methanogens. The hydrophobic permeable membranes are used as planes through the solid waste. These selective membranes are used to separate biogas and to have smooth and fast transfer of biogas from waste to the storage. The approach of this research is believed to be as a new generation of sustainable green bio-fuel biocells.

Teaching Reform and Practice of Animal Products Processing under the Background of Intelligent Agriculture

Effective food professional personnel training strategies are explored and implemented,and interdisciplinary talents of food science and engineering in accordance with the background of intelligent agriculture are cultivated from the aspects of construction of teaching staff,reform of teaching content,upgrading of teaching model,construction of industry-education integration platform,which is of great significance to the modernization development of Chinese animal products processing industry.

Research on Key Points of Design of Standard Plants in Modern Industrial Parks Under the Background of Promoting the Development of New Quality Productive Forces

With the progress of science and technology and the acceleration of industrialization,the modern industrial park is an important carrier of industrial development.The importance of its standard plant design has become increasingly prominent.With the development of new quality productive forces as the background,this research deeply discusses the key points of standard plant design in modern industrial parks.This paper uses literature review and case analysis to systematically analyze the important role of standard plant design in developing new quality productive forces in modern industrial parks and puts forward suggestions for optimizing design.It is found that the rationality,intelligence,and environmental protection of plant design are the key factors affecting the development of new quality productive forces.The paper summarizes the core points of modern industrial park standard plant design to provide a reference for the future development of related industries.

Wuxi Hongyuan: Featured with a variety of intelligent products

Wuxi Hongyuan: Featured with a variety of intelligent products Wuxi Hongyuan Electromechanical Technology Co., Ltd. is highlighted on various intelligent products, including HY-IDS Synthetic Filament Bobbin Automatic Handing System, HY-9 Automatic Doffing High- Speed Draw Texturing Machine, HY-10 Multi-Spindle High-Speed Draw Texturing Machine, and HY-6T and HY-7 High-Speed Draw Texturing Machines.

Layout and Simulation Design of Intelligent Manufacturing Production Line via Visualone

NC machining of parts and components is developing in the direction of automation and intelligence.In addition,the automatic production line puts forward higher requirements for the overall layout,technological process and production tempo.The layout and simulation of the production line can more directly reflect the problems that may occur in the operation of the production line,and solve these problems through scientific methods.This project uses VisualOne software to simulate the operation of the intelligent manufacturing production line,which can directly find the existing problems in the layout of the production line and the process of the craftsmen,and optimize the layout of the production line.In addition,it can provide reliable support for the equipment procurement and on-site construction of the intelligent manufacturing automation production line in the later stage.

Intelligent manufacture adapts to agile manufacture production mode in the 21st century

The paper describes the characteristics of the intelligent manufacturing system and production mode in the 21st century in the information age, therefore draws a conclusion that the intelligent manufacturing system adapts to agile manufacture (AM for short) production mode in the 21st century.

Multi-machine collaboration realization conditions and precise and efficient production mode of intelligent agricultural machinery

Multi-machine collaboration of agricultural machinery is one of the international frontier and hot research in the field of agricultural equipment.However,the current domestic multi-machine collaborative operation of agricultural machinery is limited to the research of task goal planning and collaborative path optimization in a single production link.In order to achieve the purpose of zero inventory of agricultural materials and precise and efficient production operations,a new technology of agricultural machinery multi-machine collaboration with multi-dimension and full chain was proposed,which takes into account the whole process of agricultural production,as well as agricultural machinery system and external supply chain,storage and transportation chain collaboration.The problems of data collaboration,process collaboration and organization collaboration were analyzed.And the realization conditions of new multi-machine cooperative technology were analyzed.Meanwhile,the zero inventory mode and precise operation mode of agricultural materials under the background of multi-machine cooperation of intelligent agricultural machinery were studied.Then,a precise and efficient agricultural production mode based on data-process-organization collaboration was constructed.The results showed that the multi-machine cooperative technology mode of multi-dimensional and full-chain agricultural machinery could greatly improve the efficiency of agricultural machinery,operation quality,land utilization rate and reduce production cost.

INTELLIGENT MECHANISM TO SUPPORT DFX ABILITIES IN AUTOMATED DESIGNER'S ENVIRONMENT

The paper aims at providing a computerized design environment to support product design practically. The authors solved this problem by taking the product life-cycle issues into consideration as more as possible during the design process from the designer-oriented perspective of view. Design for X-abilities (DFX) is an effective approach to this philosophy. So the paper mainly presents the infrastructure of an intelligent DFX mechanism which is the essential part of the developed product design environment. At first the designer-oriented computer environment DesignerSpace is introduced for understanding the designer how to implement design activities and DFX method better. In order to integrate design knowledge from downstream aspects for the optimization and the design decision-making, an intelligent DFX mechanism is developed to incorporate knowledge base, algorithm-base and monitoring/debugging tools. DesignerSpace is implemented with DFX abilities and applied to the blisk design of aircraft engine and the further development is strongly intended.

The safety parameters monitoring system for the coal mine based on CAN bus communication and intelligent data acquisition

In this paper,a monitoring and controlling system for the safety in production and environmental parameters of a small and medium-sized coal mine has been developed after analyzing the current domestic coal production and security conditions. The client computer can convert the analog signal about the safety in production and environmental parameters detected from the monitoring terminal into digital signal,and then,send the signal to the coal mine safety monitoring centre. This information can be analyzed,judged,and diagnosed by the monitoring-management-controlling software for helping the manager and technical workers to control the actual underground production and security situations. The system has many advantages including high reliability,better performance of real-time monitoring,faster data communicating and good practicability,and it can effectively prevent the occurrence of safety incidents in coal mines.

新质生产力的演化:维度、结构及路径

新质生产力体现为全方位、系统性、持续性的变革过程,其不仅能优化经济基础的应用场景和能力层级,而且能推进产业协同升级和整体跃迁,其发展进程呈现动态性和加速性,可对已有高质量发展范式、路径进行破坏性创新、爆发性升级、动态性更迭。新质生产力是“制度型生产力→干预型生产力→跨越式生产力→信息化生产力→新质生产力”和“结构型生产力→市场型生产力→可持续生产力→信息化生产力→新质生产力”的有机统一。新质生产力是对信息化生产力的继承和发展,是一种更为先进的生产力形态,具有更新颖的数智技术革命背景、更复杂的内在运作机理、更前瞻性的经济系统以及更深邃的演化路径,也更能代表生产力的最新发展趋势。

知识服务与新质生产力:双向赋能机制与实践路径

[目的/意义]新质生产力是数智背景下生产力发展的最新形态,探讨知识服务与其双向赋能的机制与实践路径,对于发挥数据要素新价值、数智技术新动能、智能服务新范式的效用,促进培育新质生产力和提升知识服务,具有重要的理论意义和现实意义。[方法/过程]本研究以总结知识服务发展历程和在新质生产力视角下的新阐释为基础,通过剖析知识服务与新质生产力双向赋能的内在关联、外在表现,构建出知识服务与新质生产力的双向赋能机制,并提出双向赋能路径。[结果/结论]“要素重组是重要抓手、科技创新是关键举措、优质服务是终极目标”成为知识服务与新质生产力双向赋能的内在关联;知识服务通过助力科学研究加速科技创新,优化跨学科跨领域知识关联与挖掘开辟新赛道,助力产业智能化转型升级孕育新业态,培育新质生产力;新质生产力通过化解资源潜在价值挖掘受限困境、技术模型算法依赖困境、人才数量与质量欠佳困境和增加需求、增长点与竞争优势驱动知识服务发展,提升知识服务。最后,通过以市场需求为导向,以数据要素为核心,以技术创新为关键,以应用场景为抓手,把握新质增长引擎,压实智能驱动底座,夯实融合应用基础,落实双向赋能机制。

发展新质生产力 推动我国经济高质量发展

中华人民共和国(新中国)成立以来,从毛泽东的《论十大关系》,到邓小平的“科学技术是第一生产力”,再到习近平的“整合科技创新资源,引领发展战略性新兴产业和未来产业,加快形成新质生产力”,我党对经济工作规律性的认识,随着时代的发展而不断深化。习近平总书记在2024年1月31日召开的中央政治局第十一次集体学习会议上的重要讲话,更是把这种认识推向了全新的高度。总书记在主持学习时明确指出“必须牢记高质量发展是新时代的硬道理”,“高质量发展需要新的生产力理论来指导,而新质生产力已经在实践中形成并展示出对高质量发展的强劲推动力、支撑力,需要我们从理论上进行总结、概括,用以指导新的发展实践”,并强调“科技创新能够催生新产业、新模式、新动能,是发展新质生产力的核心要素”。为了深入学习贯彻总书记讲话精神,围绕“发展新质生产力推动我国经济高质量发展”这个新时代经济发展的核心课题,本刊邀请国内著名专家、学者,撰写一组笔谈文章,以飨读者。