Layout Planning Technology of Cellular Manufacturing System Based on Process Interconnection Analysis

With sustaining change of production mode,layout planning is no longer a thing built once for all.Cellular layout(CL) is becoming a hotspot in the research field of manufacturing system layout.Traditional researches on layout planning are mainly concentrating on aspects of layout arithmetic,style and evaluation,etc.Relatively seldom efforts are paid to CL and its specific problems as cell formation(CF),equipment sharing and CL analysis.Through problem analyzing of layout in cellular manufacturing system(CMS),research approach of cell formation,interactive layout and layout analysis threaded with process interconnection relationship(PIR) is proposed.Typical key technologies in CL like CF technology based on similarity analysis of part processes,interactive visual layout technology,layout evaluation technology founded on PIR analysis and algorithm of cell equipment sharing are put forward.Against the background of one enterprise which encounters problems of low utility of key equipments and disperse material logistic,an example of four-cell layout is given.The CL adjustment and analysis results show that equipment with high level of sharing degree should be disposed around the boundary of its main cell,and be near to other sharing cells as possible; process route should be centralized by all means,so equipment adjustment is to be implemented along direction that route intersection can be decreased; giving consideration to the existence of discrete cell,logistic route and its density should be centralized to cells formed.The proposed research can help improve equipment utility and material logistic efficiency of CL,and can be popularized to other application availably.

Influence of manufacturing process-induced geometrical defects on the energy absorption capacity of polymer lattice structures

Modern additive manufacturing processes enable fabricating architected cellular materials of complex shape,which can be used for different purposes.Among them,lattice structures are increasingly used in applications requiring a compromise among lightness and suited mechanical properties,like improved energy absorption capacity and specific stiffness-to-weight and strength-to-weight ratios.A dedicated modeling strategy to assess the energy absorption capacity of lattice structures under uni-axial compression loading is presented in this work.The numerical model is developed in a non-linear framework accounting for the strain rate effect on the mechanical responses of the lattice structure.Four geometries,i.e.,cubic body centered cell,octet cell,rhombic-dodecahedron and truncated cuboctahedron 2+,are investigated.Specifically,the influence of the relative density of the representative volume element of each geometry,the strain-rate dependency of the bulk material and of the presence of the manufacturing process-induced geometrical imperfections on the energy absorption capacity of the lattice structure is investigated.The main outcome of this study points out the importance of correctly integrating geometrical imperfections into the modeling strategy when shock absorption applications are aimed for.

Multi-sensor measurement and data fusion technology for manufacturing process monitoring:a literature review

Due to the rapid development of precision manufacturing technology,much research has been conducted in the field of multisensor measurement and data fusion technology with a goal of enhancing monitoring capabilities in terms of measurement accuracy and information richness,thereby improving the efficiency and precision of manufacturing.In a multisensor system,each sensor independently measures certain parameters.Then,the system uses a relevant signalprocessing algorithm to combine all of the independent measurements into a comprehensive set of measurement results.The purpose of this paper is to describe multisensor measurement and data fusion technology and its applications in precision monitoring systems.The architecture of multisensor measurement systems is reviewed,and some implementations in manufacturing systems are presented.In addition to the multisensor measurement system,related data fusion methods and algorithms are summarized.Further perspectives on multisensor monitoring and data fusion technology are included at the end of this paper.

Advancements in machine learning for material design and process optimization in the field of additive manufacturing

Additive manufacturing technology is highly regarded due to its advantages,such as high precision and the ability to address complex geometric challenges.However,the development of additive manufacturing process is constrained by issues like unclear fundamental principles,complex experimental cycles,and high costs.Machine learning,as a novel artificial intelligence technology,has the potential to deeply engage in the development of additive manufacturing process,assisting engineers in learning and developing new techniques.This paper provides a comprehensive overview of the research and applications of machine learning in the field of additive manufacturing,particularly in model design and process development.Firstly,it introduces the background and significance of machine learning-assisted design in additive manufacturing process.It then further delves into the application of machine learning in additive manufacturing,focusing on model design and process guidance.Finally,it concludes by summarizing and forecasting the development trends of machine learning technology in the field of additive manufacturing.

Research Progress of Additive Manufacturing Technology in Energetic Material Field at Home and Abroad

As a subversive manufacturing technology, additive manufacturing technology has many technical advantages such as high freedom of design and not limited by complex structure of parts. The application of additive manufacturing technology to the charge molding of energetic materials will subvert the traditional manufacturing concept of energetic materials, realize the advanced charge design concept, shorten the research and development time of weapons and equipment, and improve the comprehensive performance of weapons and equipment, which is of great significance for the rapid development of high-tech weapons and equipment. This paper analyzes the research progress of additive manufacturing technology in the field of energetic materials at home and abroad and puts forward some suggestions for future research of this technology. .

A HybridManufacturing ProcessMonitoringMethod Using Stacked Gated Recurrent Unit and Random Forest

This study proposed a new real-time manufacturing process monitoring method to monitor and detect process shifts in manufacturing operations.Since real-time production process monitoring is critical in today’s smart manufacturing.The more robust the monitoring model,the more reliable a process is to be under control.In the past,many researchers have developed real-time monitoring methods to detect process shifts early.However,thesemethods have limitations in detecting process shifts as quickly as possible and handling various data volumes and varieties.In this paper,a robust monitoring model combining Gated Recurrent Unit(GRU)and Random Forest(RF)with Real-Time Contrast(RTC)called GRU-RF-RTC was proposed to detect process shifts rapidly.The effectiveness of the proposed GRU-RF-RTC model is first evaluated using multivariate normal and nonnormal distribution datasets.Then,to prove the applicability of the proposed model in a realmanufacturing setting,the model was evaluated using real-world normal and non-normal problems.The results demonstrate that the proposed GRU-RF-RTC outperforms other methods in detecting process shifts quickly with the lowest average out-of-control run length(ARL1)in all synthesis and real-world problems under normal and non-normal cases.The experiment results on real-world problems highlight the significance of the proposed GRU-RF-RTC model in modern manufacturing process monitoring applications.The result reveals that the proposed method improves the shift detection capability by 42.14%in normal and 43.64%in gamma distribution problems.

Research on the Impact of Digital Technology and Servitization on the Performance of Manufacturing Enterprises

This article mainly discusses the impact of digital technology and service-oriented on the performance of manufacturing enterprises.It first elaborates on the background of the trend of service-oriented manufacturing and the significance of its enterprises.Then,based on the impact of digital technology on the performance of manufacturing enterprises,several practical and feasible measures are proposed,mainly focusing on the long-term layout of service-oriented,shortening the low period,enhancing the competitive awareness of state-owned manufacturing enterprises,improving the driving force transformation,achieving simultaneous progress digitally,configuring digital and service-oriented elements,and eliminating the monopoly of digital resources.Followed by lowering the threshold for private enterprise resource acquisition,promoting financial digital development,breaking the financial dilemma of service-oriented manufacturing,continuously improving the performance level of manufacturing enterprises,and promoting the development of manufacturing enterprises.

Robust interface and excellent as-built mechanical properties of Ti–6Al–4V fabricated through laser-aided additive manufacturing with powder and wire

The feasibility of manufacturing Ti-6Al-4V samples through a combination of laser-aided additive manufacturing with powder(LAAM_(p))and wire(LAAM_(w))was explored.A process study was first conducted to successfully circumvent defects in Ti-6Al-4V deposits for LAAM_(p) and LAAM_(w),respectively.With the optimized process parameters,robust interfaces were achieved between powder/wire deposits and the forged substrate,as well as between powder and wire deposits.Microstructure characterization results revealed the epitaxial prior β grains in the deposited Ti-6Al-4V,wherein the powder deposit was dominated by a finerα′microstructure and the wire deposit was characterized by lamellar α phases.The mechanisms of microstructure formation and correlation with mechanical behavior were analyzed and discussed.The mechanical properties of the interfacial samples can meet the requirements of the relevant Aerospace Material Specifications(AMS 6932)even without post heat treatment.No fracture occurred within the interfacial area,further suggesting the robust interface.The findings of this study highlighted the feasibility of combining LAAM_(p) and LAAM_(w) in the direct manufacturing of Ti-6Al-4V parts in accordance with the required dimensional resolution and deposition rate,together with sound strength and ductility balance in the as-built condition.

Exploration and Application Practice of Energy Conservation Theory and Method in Steel Manufacturing Process System

This article briefly discusses the theoretical basis and overall goals of energy conservation in the steel manufacturing process system.It is proposed that in the process of implementing system energy conservation,it is necessary to fully recognize and utilize the characteristics and functional advantages of the steel manufacturing process,pay more attention to energy quality,firmly grasp the overall goal of system optimization,focus on the integrated optimization of gas,steam,and waste heat systems,and propose the idea of constructing a"steel chemi-cal gas electricity heating cooling multi generation system".Based on practice,the main principles,models,and effects of implementing systematic energy conservation in steel enterprises have been proposed.

Study on the Collaboration between Advanced Manufacturing Technology and Production Process

The advanced manufacturing technology of mechanical products features interaction, and high simulation, etc. In this paper, a digital geometry model for the processing is established with the aid of computer technology, so that the needs of machinery manufacturing production and precision machining can be fulfilled, and also the simulation, validation, comparison, and optimization of many plans can be implemented for ultimately finding out an optimal processing method and realizing the benefit of low cost and high quality. From two different levels of activity and parts, the configuration principle of mechanical products＇ advanced manufacturing technology is defined. Therefore, the advanced manufacturing technology for customizing different products can be derived, and also the reuse of different types of parts is realized. Finally, this is verified with an example.

Microstructure of TA2/TA15 graded structural material by laser additive manufacturing process

TA2/TA15 graded structural material（GSM） was fabricated by the laser additive manufacturing（LAM） process. The chemical composition, microstructure and micro-hardness of the as-deposited GSM were investigated. The results show that the TA2 part of exhibiting near-equiaxed grains was Widmanst？tten α-laths microstructure. The TA15 part containing large columnar grains was fine basket-weave microstructure. The graded zone was divided into four deposited layers with 3000 μm in thickness. As the distance from the TA2 part increases, the alloy element contents and the β phase volume fraction increase, the α phase volume fraction decreases and the microstructure shows the evolution from Widmanst？tten α-laths to basket-weave α-laths gradually. The micro-hardness increases from the TA2 part to the TA15 part due to the solid solution strengthening and grain boundary strengthening.

WEB-BASED MANUFACTURING PROCESS DEVELOPER

Product and manufacturing process developments are knowledge intensive. For rapid product developments in today′s competitive global marketplace, we need tools to facilitate the effective utilization of critical design and manufacturing knowledge obtained during the previous product developments. The Internet technology has very rapidly evolved over past few years. The web is being increasingly used to support various activities of the pro duct development process. Java is a programming language that is highly tuned for the web environment. This paper is concerned with providing the solution of web based manufacturing process development. The architecture of web based application and the implementation of web based manufacturing process developer are discussed.

Fundamental Theories and Key Technologies for Smart andOptimal Manufacturing in the Process Industry

Given the significant requirements for transforming and promoting the process industry, we present themajor limitations of current petrochemical enterprises, including limitations in decision-making, produc-tion operation, efficiency and security, information integration, and so forth. To promote a vision of theprocess industry with efficient, green, and smart production, modern information technology should beutilized throughout the entire optimization process for production, management, and marketing. To focuson smart equipment in manufacturing processes, as well as on the adaptive intelligent optimization of themanufacturing process, operating mode, and supply chain management, we put forward several key scien-tific problems in engineering in a demand-driven and application-oriented manner, namely：intelligentsensing and integration of all process information, including production and management information; collaborative decision-making in the supply chain, industry chain, and value chain, driven by knowledge; cooperative control and optimization of plant-wide production processes via human-cyber-physical in-teraction; and Q life-cycle assessments for safety and environmental footprint monitoring, in addition totracing analysis and risk control. In order to solve these limitations and core scientific problems, we furtherpresent fundamental theories and key technologies for smart and optimal manufacturing in the processindustry. Although this paper discusses the process industry in China, the conclusions in this paper can beextended to the larocess industry around the world.

A Perspective on Smart Process Manufacturing Research Challenges forProcess Systems Engineers

The challenges posed by smart manufacturing for the process industries and for process systems engineering（PSE） researchers are discussed in this article. Much progress has been made in achieving plant- and site-wide optimization, hut benchmarking would give greater confidence. Technical challenges confrontingprocess systems engineers in developing enabling tools and techniques are discussed regarding flexibilityand uncertainty, responsiveness and agility, robustness and security, the prediction of mixture propertiesand function, and new modeling and mathematics paradigms. Exploiting intelligence from big data to driveagility will require tackling new challenges, such as how to ensure the consistency and confidentiality ofdata through long and complex supply chains. Modeling challenges also exist, and involve ensuring that allkey aspects are properly modeled, particularly where health, safety, and environmental concerns requireaccurate predictions of small but critical amounts at specific locations. Environmental concerns will requireus to keep a closer track on all molecular species so that they are optimally used to create sustainablesolutions. Disruptive business models may result, particularly from new personalized products, but that isdifficult to predict.

Calculating Method for Influence of Material Flow on Energy Consumption in Steel Manufacturing Process

From the viewpoint of systems energy conservation, the influences of material flow on its energy consumption in a steel manufacturing process is an important subject. The quantitative analysis of the relationship between material flow and the energy intensity is useful to save energy in steel industry. Based on the concept of standard material flow diagram, all possible situations of ferric material flow in steel manufacturing process are analyzed. The expressions of the influence of material flow deviated from standard material flow diagram on energy consumption are put forward.

Opportunities and Challenges of Artificial Intelligence for Green Manufacturing in the Process Industry

Smart manufacturing is critical in improving the quality of the process industry. In smart manufacturing, there is a trend to incorporate different kinds of new-generation information technologies into process- safety analysis. At present, green manufacturing is facing major obstacles related to safety management, due to the usage of large amounts of hazardous chemicals, resulting in spatial inhomogeneity of chemical industrial processes and increasingly stringent safety and environmental regulations. Emerging informa- tion technologies such as arti cial intelligence (AI) are quite promising as a means of overcoming these dif culties. Based on state-of-the-art AI methods and the complex safety relations in the process industry, we identify and discuss several technical challenges associated with process safety: ① knowledge acquisition with scarce labels for process safety;② knowledge-based reasoning for process safety;③ accurate fusion of heterogeneous data from various sources;and ④ effective learning for dynamic risk assessment and aided decision-making. Current and future works are also discussed in this context.

Advanced Data Collection and Analysis in Data‑Driven Manufacturing Process

The rapidly increasing demand and complexity of manufacturing process potentiates the usage of manufacturing data with the highest priority to achieve precise analyze and control,rather than using simplified physical models and human expertise.In the era of data-driven manufacturing,the explosion of data amount revolutionized how data is collected and analyzed.This paper overviews the advance of technologies developed for in-process manufacturing data collection and analysis.It can be concluded that groundbreaking sensoring technology to facilitate direct measurement is one important leading trend for advanced data collection,due to the complexity and uncertainty during indirect measurement.On the other hand,physical model-based data analysis contains inevitable simplifications and sometimes ill-posed solutions due to the limited capacity of describing complex manufacturing process.Machine learning,especially deep learning approach has great potential for making better decisions to automate the process when fed with abundant data,while trending data-driven manufacturing approaches succeeded by using limited data to achieve similar or even better decisions.And these trends can demonstrated be by analyzing some typical applications of manufacturing process.

Simulation Based Energy-resource Efficient Manufacturing Integrated with In-process Virtual Management

As energy efficiency is one of the key essentials towards sustainability, the development of an energy-resource efficient manufacturing system is among the great challenges facing the current industry. Meanwhile, the availability of advanced technological innovation has created more complex manufacturing systems that involve a large variety of processes and machines serving different functions. To extend the limited knowledge on energy-efficient scheduling, the research presented in this paper attempts to model the production schedule at an operation process by considering the balance of energy consumption reduction in production, production work flow （productivity） and quality. An innovative systematic approach to manufacturing energy-resource efficiency is proposed with the virtual simulation as a predictive modelling enabler, which provides real-time manufacturing monitoring, virtual displays and decision-makings and consequentially an analytical and multidimensional correlation analysis on interdependent relationships among energy consumption, work flow and quality errors. The regression analysis results demonstrate positive relationships between the work flow and quality errors and the work flow and energy consumption. When production scheduling is controlled through optimization of work flow, quality errors and overall energy consumption, the energy-resource efficiency can be achieved in the production. Together, this proposed multidimensional modelling and analysis approach provides optimal conditions for the production scheduling at the manufacturing system by taking account of production quality, energy consumption and resource efficiency, which can lead to the key competitive advantages and sustainability of the system operations in the industry.

Research on Cloud Manufacturing Resource-Aware and Access Technology Using RFID

With the continuous development of cloud manufacturing technology,in order to solve more complex manufacturing problem and conduct large-scale networked manufacturing,combining with the characteristic of discrete manufacturing enterprise's demands and RFID( Radio Frequency Identification),a kind of RFIDbased cloud manufacturing resource-aware and access technology is proposed. Firstly,the architecture of the cloud manufacturing system and RFID system is briefly introduced. Then,the key technologies of manufacturing resource-aware and access technology are analyzed,including anti-collision technology,reader management technology and so on. Finally,taking the manufacturing of the key components in discrete manufacturing enterprise as an example,the practicality and feasibility of the technology is verified. The results show that the application of this technology provides a strong guarantee for the sharing and collaboration of manufacturing resources and capacity in the discrete manufacturing industry.

Operation optimization of the steel manufacturing process: A brief review

Against the realistic background of excess production capacity, product structure imbalance, and high material and energy consumption in steel enterprises, the implementation of operation optimization for the steel manufacturing process is essential to reduce the production cost, increase the production or energy efficiency, and improve production management. In this study, the operation optimization problem of the steel manufacturing process, which needed to go through a complex production organization from customers' orders to workshop production, was analyzed. The existing research on the operation optimization techniques, including process simulation, production planning, production scheduling, interface scheduling, and scheduling of auxiliary equipment, was reviewed. The literature review reveals that, although considerable research has been conducted to optimize the operation of steel production, these techniques are usually independent and unsystematic.Therefore, the future work related to operation optimization of the steel manufacturing process based on the integration of multi technologies and the intersection of multi disciplines were summarized.