Process For Production Of Parts Research Articles

The Synergy Model of Quality Tools and Methods and Its Influence on Process Performance and Improvement

Implementing quality tools and methods creates a basic foundation for innovations, sustainability, optimization, and competitiveness in the era of Industry 4.0 and Quality 4.0. This paper aimed to investigate the use of quality tools and methods in the 24 divisions of a mother manufacturing company without the influence of external factors such as geographical location (America, Africa, Asia, and Europe). It was important for the mother manufacturing company to implement a uniform process standard for innovation and performance. Research methods focused on using the Kanban card, Ishikawa diagram, affinity diagram, Flowchart, 5S, OPL, layout, and Pareto analysis. It was determined in this research that the synergy (combination) of quality tools and methods in divisions improves the process performance. This hypothesis was confirmed by the results of implementing quality tools in processes within divisions. A top result was the new innovative model of synergy of the quality tools and methods for divisions of the parent company thus filling a gap in the scientific field. This model created the basis for the uniform process standard in all divisions. The results brought improvements in the processes such as material input inspection, spare parts production, production process, and product packaging. This model could be a proactive instrument for process innovation.

Combination of value stream mapping (VSM) method and kanban system to reduce time waste in the production process of making parts for the four-wheel vehicle industry

Fulfilling orders from customers in the automotive industry is a necessity that inevitably causes problems that arise in product delivery to customers due to production delays and decreased production yields. The production process often experiences wasted time in the production process of four-wheeled vehicle spare parts. This research aims to reduce production process time, provide solutions to reduce waste and increase the number of four-wheeled vehicle spare parts produced. This research method uses the Lean Manufacturing (LM) approach by combining the Value Stream Mapping (VSM) method with Kanban system improvements, the application of Root Cause Analysis (RCA), and the Kaizen method. This research found that four factors cause waste in process time, including environmental factors, methods, humans, and machines. This research produces the right solution in the relay out of the Assembly and Final Inspection production processes, as well as the use of the e-kanban system in material and product inventory. The research results have reduced the production process time from 17.10 days to 10.05 days, meaning a decrease of 41.22%. This affected production results which increased from an average monthly production of 42,917 pcs to 60,157 pcs, meaning an increase of 128.65%.

A novel approach of online monitoring for laser powder bed fusion defects: Air-borne Acoustic Emission and Deep Transfer Learning

Defects in laser powder bed fusion (L-PBF) are a serious constraint on the application of the technology. Developing a real-time monitoring technology to guide the production process of parts can solve this problem. Currently, the quality of L-PBF with different scanning strategies varies greatly. Therefore, the online monitoring methods for a specific scanning strategy cannot be effectively generalized to other scanning strategies. This is a rarely investigated topic in L-PBF, and defects monitoring mechanism research is insufficient to effectively support the study of L-PBF defects monitoring technology utilizing advanced sensing technologies. Towards this end, we explored the acoustic source generation mechanism, analyzed the acoustic monitoring principle of L-PBF defects, and hence, we propose a novel online monitoring method for L-PBF defects based on air-borne acoustic emission (ABAE) and deep transfer learning (DTL). The method uses time-frequency spectrograms of acoustic signals as the input to the network, and a method of deep transfer learning with multi-source domains knowledge fusion (DTL-MDKF) is proposed to realize the classification of defects. The proposed method was compared with the traditional transfer learning method based on single-source domain knowledge. The results showed that the classification accuracy of the proposed method for L-PBF defects is 98.2 %. In addition, the feature mining capability of the DTL-MDKF is demonstrated by visualizing the features of transfer learning models with different knowledge. Looking at the results, the proposed method can be considered a promising L-PBF defects online monitoring method for complex and changeable working conditions.

Simulation of Auto Parts Polishing Control Strategy Based on PID Control

With the large increase in automobile production, the demand for automobile parts is also increasing day by day. Aluminum alloy is the most widely used material in automobile parts. The production process of aluminum alloy parts has been automated, but the polishing process is still mainly manual. The high cost and low efficiency of manual polishing restrict the development of parts production technology. Therefore, it is imperative to develop a set of automatic polishing systems for aluminum alloy parts. Robot application in the polishing field has become a trend, but the force/bit coupling relationship in the polishing process of a robot is complicated, which brings great difficulty to the control of the polishing force. To solve the above problems, the key to obtaining stable polishing quality is to realize the force/bit decoupling of robot polishing and control the output constant polishing force. In this paper, an end-effector is used to realize the decoupling of force and position, and a new constant-force polishing control strategy is proposed to improve the automatic control level of robot polishing aluminum alloy auto parts. According to the nonlinear characteristics of the end-effector mathematical model and the feedback linearization characteristics of the backstepping method, a new type of backstepping PID constant force controller is designed, and the control flow is set up for simulation analysis. Simulink was used to build the simulation process and set up a reasonable controller gain for simulation verification. The simulation results of end-effector output polishing force under different strategies show that the reverse PID control has better response speed and anti-interference ability than the simple reverse control.

Material variability effects on automotive part production process

The current efforts to reduce the carbon footprint throughout the chain in the automotive industry by increased use of recycled materials poses new challenges for materials production and their use. The increase of steel scrap fraction in the current primary steel making processes, used for producing steel sheet metal for automotive components, possibly affects the material properties variability beyond the limits observed in the materials produced today despite mitigating actions in steel production. In this paper material variability increase was modelled by selecting deterministic values outside the range of the material grade used to design and manufacture an automotive part. The values were selected from an experimental data set representing the cold rolled mild steels material class range. The effects were studied numerically on a reverse engineered model of an existing automotive part production process. It was found that the manufacturing feasibility in this particular case is mainly affected by the weighted average plastic strain ratio and less by the degree of planar anisotropy.

Analysis and Prediction of Roughness of Face Milled Surfaces using CAD Model

The condition for the designability and efficiency of the machining processes is that the part production process is chosen to meet the operational requirements based on the most accurate technological plans possible. One part of this is the planning of the required quality and roughness of the surfaces and achievement of the required values in the finishing. In this paper, a study on the predictability of surface roughness was performed using a CAD model based on theoretical roughness and validated by cutting experiments. The reported results show the effect of the feed rate change in face milling for two tools with different edge geometries in planes parallel to the feed direction.

In-situ monitoring of powder bed fusion of metals using eddy current testing

Powder bed fusion of metals (PBF-LB/M) is the most commonly used additive manufacturing process for the layerwise production of metal parts. Although the technology has developed rapidly in recent years, manufactured parts still lack consistent quality primarily owing to process-inherent variability, and the lack of effective sensing technologies enabling the ability to control the process during part production. Thus, there are high costs caused by rigorous post-process part inspection steps required to provide compliant part certificates. In contrast to typically deployed in-situ sensing technologies, eddy current testing (ECT) is a standardized nondestructive testing (NDT) technique able to provide compliant part certificates during post-process inspection according to existing standards. This study investigates the potential of ECT as an in-situ process monitoring technology for PBF-LB/M. Parts made from AlSi10Mg were manufactured on a PBF-LB/M machine using different process parameters yielding different relative densities ranging from 99%– 99.7%. During the build cycle, the parts were measured layer-by-layer with an ECT system mounted on the machine recoater. Signal analysis methods were developed which effectively separate and calibrate the electrical conductivity component (relative electrical conductivity) and the distance component (lift-off) of the ECT signals. The relative electrical conductivity was then compared to X-ray micro-computed tomography ( μ CT) measurement data demonstrating that layer-to-layer differences in relative density of about 0.1% can be successfully detected via ECT. In addition, the lift-off was used to monitor the thickness of the consolidated layers and the layer-to-layer part height. The results show that ECT is an effective technology for in-situ monitoring of the relative part density paving the way for deploying ECT for in-situ NDT of PBF-LB/M-manufactured parts.

Modeling, Analysis, and Improvement of Batch-Discrete Manufacturing Systems: A Systems Approach

Production systems include both discrete part and batch operations, where an individual part is manufactured in a discrete operation, and a group of parts are processed simultaneously, i.e., in a batch, on one machine for a batch operation. Many manufacturing industries, such as battery, aircraft, and automotive, consist of mixed batch and discrete part operations, referred to as batch-discrete lines. Although such operations are widely encountered, analytical studies of these systems are limited in current literature. In this paper, a systems approach is presented to model and analyze batch-discrete lines. First, a Bernoulli machine reliability model for a two-machine batch-discrete system is introduced. Using a virtual buffer to represent the batch processing feature, performance evaluation formulae are derived and system properties are investigated. Using them, improvement analyses and bottleneck identification are presented. Then, the model is extended to systems with a quality inspection device under different control policies. To illustrate the applicability of the model, a case study in a composite part production process is described. Such a work delivers a quantitative tool for production engineers and managers to design, analyze, and improve batch-discrete manufacturing systems. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Many manufacturing systems in aircraft, automotive, battery, medical device, and defense industries include both batch operation and discrete part processing machines. In a batch operation, multiple parts are manufactured simultaneously on a batch machine, while a single part is made in a discrete part machine. Production lines with mixed batch and discrete part operations are named as batch-discrete systems. Analysis and improvement of such systems are critical to ensure high productivity and quality. However, accurate modeling and analysis of batch-discrete systems are lacking in current literature. To bridge this gap, a novel methodology is presented in this paper. Using a Bernoulli reliability machine model with a virtual buffer concept, performance measures are derived for batch-discrete two-machine lines, as well as the reversed discrete-batch lines. Then system properties, such as monotonicity, interchangeability, and reversibility, are investigated, followed by improvement analysis under constraints and bottleneck analysis. By extending to systems with quality inspections, two quality control policies, to scrap either the current batch or the whole inventory after detecting a degraded part, are studied. In addition, a case study of heating (batch) and trimming (discrete) operations in composite panel production lines is presented, and improvement strategies are investigated, to illustrate how to apply the model and analysis in practice.

Radio Frequency Identification (RFID) based wireless manufacturing systems, a review

Radio frequency identification (RFID) is one of the most promising technological innovations in order to track and trace products as well as material flow in manufacturing systems. High Frequency (HF) and Ultra High Frequency (UHF) RFID systems can track a wide range of products in the part production process via radio waves with level of accuracy and reliability. As a result, quality and transparency of data across the supply chain can be accurately obtained in order to decrease time and cost of part production. Also, process planning and part production scheduling can be modified using the advanced RFID systems in part manufacturing process. Moreover, to decrease the cost of produced parts, material handling systems in the advanced assembly lines can be analyzed and developed by using the RFID. Smart storage systems can increase efficiency in part production systems by providing accurate information from the stored raw materials and products for the production planning systems. To increase efficiency of energy consumption in production processes, energy management systems can be developed by using the RFID-sensor networks. Therefore, smart factories and intelligent manufacturing systems as industry 4.0 can be introduced by using the developed RFID systems in order to provide new generation of part production systems. In this paper, a review of RFID based wireless manufacturing systems is presented and future research works are also suggested. It has been observed that the research filed can be moved forward by reviewing and analyzing recent achievements in the published papers.

Production and measuring methods and procedures in precision optical cavities production

This work presents the development of the production process of individual parts of the Fabry-Perot type laser resonator. It describes the acquired knowledge in the field of production of very precise optical standards, cavities, and lenses. In addition, it describes the measurement methods used in production. The work is intended for industry and science.

Research on Visual Inspection Method and Instrument of Solder Joint

Due to the instability of stamping and welding process, there will be missing welding in the production process of auto parts, and multiple welding spots appear on the multi angle joint surface of the workpiece. However, the manual detection is inefficient and the accuracy is poor, and the leakage often occurs in the above situations. In view of the above problems, an intelligent detection algorithm of solder joints based on deep learning YOLOv3 framework is proposed. The machine vision equipment for inspecting solder joint is built, and the welding spot inspection experiment is carried out on the platform. A large number of welding spot images are collected and samples are enhanced to obtain different sample data. By comparing this method with the Hough circle transform for circle fitting of solder joints in the image, the experimental results show that the proposed deep learning-based YOLOv3 framework solder joint detection effect is better.

Production Process Control for Aero Engine Part Manufacturing

This paper presents a method for production process control for aero engine part manufacturing based on product quality problem identification and statistical process control. A framework is provided. The control flow of the method is developed. The proposed method applies single value moving range control chart to monitor the production process of aero engine parts. An application case is provided. The results of the case study indicate the quality improvement of the products produced. The research can provide a reference for companies in aviation industry in China to apply control charts to monitor and control production processes for product quality improvement.

Molds with Advanced Materials for Carbon Fiber Manufacturing with 3D Printing Technology.

Fused Deposition Modeling (FDM) 3D printing is the most widespread technology in additive manufacturing worldwide that thanks to its low costs, finished component applications, and the production process of other parts. The need for lighter and higher-performance components has led to an increased usage of polymeric matrix composites in many fields ranging from automotive to aerospace. The molds used to manufacture these components are made with different technologies, depending on the number of pieces to be made. Usually, they are fiberglass molds with a thin layer of gelcoat to lower the surface roughness and obtain a smooth final surface of the component. Alternatively, they are made from metal, thus making a single carbon fiber prototype very expensive due to the mold build. Making the mold using FDM technology can be a smart solution to reduce costs, but due to the layer deposition process, the roughness is quite high. The surface can be improved by reducing the layer height, but it is still not possible to reach the same degree of surface finish of metallic or gelcoat molds without the use of fillers. Thermoplastic polymers, also used in the FDM process, are generally soluble in specific solvents. This aspect can be exploited to perform chemical smoothing of the external surface of a component. The combination of FDM and chemical smoothing can be a solution to produce low-cost molds with a very good surface finish.

Classification of research and applications of the computer aided process planning in manufacturing systems

The Computer Aided Process Planning (CAPP) systems are recently developed in manufacturing engineering to provide links between Computer Aided Design (CAD) and Computer Aided Manufacturing (CAM) systems. The CAPP systems are developed by considering the different issues of computer applications in production engineering. Optimization techniques can be applied to the CAPP to increase efficiency in part production processes. The energy consumption of part production process can be analyzed and optimized using the CAPP systems in order to increase added value in the part manufacturing process. Also, artificial neural networks as well as cloud manufacturing systems can be applied to the CAPP systems to share advantages of the different CAPP systems in different industry applications. Flexible process planning systems are developed using dynamic CAPP in order to cope with product varieties in process of part production. To develop potential energy saving strategies during product design and process planning stages, the advanced CAPP systems can be used. In this paper, a review of Computer Process Planning systems (CAPP) is presented and future research works are also suggested. It has been observed that the research filed can be moved forward by reviewing and analyzing recent achievements in the published papers.

Исследование влияния режимов постобработки на свойства поверхности деталей, изготовленных с применением аддитивных технологий

It is shown that due to peculiarities of the production process of polymer material parts using methods of additive technologies, it is required to carry out post-processing of the surface of the products. The main methods of post-processing, the influence of modes on the properties of the surface and material of the part are considered. The optimal modes and methods of post-processing of parts made of ABS-plastic by FDM-printing methods are shown.

MONITORING OF PRODUCTION PROCESSES OF RAILWAY TRANSPORT ENTERPRISES

The publication proposes a monitoring technology for production automation based on automatic identification technologies, which will allow real-time monitoring of the progress of technological processes, ensure interdepartmental logistics, as well as perform access and identification security functions in production. On the example of one of the carriage depots, typical shortcomings of the organization of the production process, accounting and identification of parts of a railway transport enterprise are considered. The ways and stages of implementation of automatic identification technologies are proposed, in particular, it is indicated that it is advisable to introduce a system for monitoring production processes of railway transport enterprises in stages, starting with bar-coding technologies. The process of monitoring railway transport enterprises, the interaction of subjects and objects of the production process is disclosed in detail.

Condition Monitoring of Manufacturing Processes under Low Sampling Rate

Manufacturing processes can be monitored for anomalies and failures just like machines, in condition monitoring and prognostic and health management. This research takes inspiration from condition monitoring and prognostic and health management techniques to develop a method for part production process monitoring. The contribution brought by this paper is an automated technique for process monitoring that works with low sampling rates of 1/3Hz, a limitation that comes from using data provided by an industrial partner and acquired from industrial manufacturing processes. The technique uses kernel density estimation functions on machine tools spindle load historical time signals for distribution estimation. It then uses this estimation to monitor the manufacturing processes for anomalies in real time. A modified version was tested by our industrial partner on a titanium part manufacturing line.

Lightweight Interleaved Residual Dense Network for Gas Identification of Industrial Polypropylene Coupled With an Electronic Nose

Polypropylene (PP) is one of the raw materials to produce automotive interior parts. Under the high-temperature condition, the volatile gas of PP will have a pungent odor. Therefore, an effective gas detection method should be proposed. In this work, a lightweight interleaved residual dense network (LIRD) is proposed and coupled with an electronic nose (e-nose) to classify the volatile gas of industrial PP used in the automotive interior. The LIRD combines the lightweight interleaved group convolution (LIGC) and residual dense network (RDN). The LIGC module is proposed to effectively reduce the number of parameters in the convolution calculation and realize the information exchange among channels. To avoid the feature degradation, RDN is introduced to fuse the shallow and deep features, and the parameters are trained adaptively to enhance the classification stability. By means of the self-developed e-nose system, the volatile gas of two PP materials (2240 S and 1120 K) is detected under different temperature gradients. Compared with other deep learning methods, the LIRD has a better classification result of 99.20% and 99.00%, the best F1-score is 0.9920 and 0.9900, and the best Kappa coefficient is 0.9900 and 0.9875 in two PP materials. The results show that the combination of LIRD and e-nose is demonstrated as an effective analytical technique for quality monitoring in the industrial production process of automotive interior parts.

Експериментальне дослідження процесу глибинного шліфування нахиленими тонкими абразивними кругами зовнішніх циліндричних поверхонь деталей

Aim. Experimental investigation of grinding of external cylindrical surfaces of parts by thin abrasive wheels that are inclined to working surface. Methods. The investigation was carried out using the methods of cutting theory, the planning of experiments, statistical processing of experimental results. Results. The thin reinforced abrasive wheels (heightened circular speed gives for these wheels) are proposed to use to work up outer cylindrical surfaces of parts with covering heightened wear resistance and hardness or the details that were received of hard-to-machine materials. The influence of the cutting modes in the production process by thin abrasive wheels on the amount of effective power and the main component of the cutting force during the processing of external cylindrical surfaces of parts were experimentally determined. The empirical relations between production modes and power parameters of the production process were defined for oncoming directions and passing directions of circular speed for the machined cylindrical part and thin abrasive wheel. Scientific novelty. The ratio of production mode by thin inclined abrasive wheels on the effective cutter power and the main component of the cutting force during the processing of external cylindrical surfaces of parts, which were experimentally received, determines that accompanying processing by the increase of cutting depth and circular speed of rotation is accompanied to increase of effective cutter power and the main component of cutting force, and the increase of the longitudinal feed is accompanied to reduce them, but effective cutter power and the main component of cutting force increase during the growth of a feed and circular speed of the part for counter processing, however, these values reduce during the increase of cutting depth. The compatible, paired influence of several factors of processing modes on the power parameters of the process is important during the production process by the inclined thin abrasive wheel. The production process concerns processes with low energy consumption. The effective cutting power does not exceed 0.45 kW for all combinations of cutting modes. Low effective cutting power together with a small contact area of the abrasive wheel with the workpiece determine a small effect on the treated surface of the heating temperature in the processing area that ensures the preservation of the mechanical characteristics of the surface layer, which was obtained in the previous stages of manufacturing the part. Low energy consumption of the production process of cylindrical parts by inclined thin abrasive wheels determines the availability of its practical use. Practical significance. The production process of cylindrical workpiece surface of hard-to-process materials or with thick-layer wear-resistant coatings, which have significant previous surface irregularities, by inclined thin abrasive wheels was proposed to use on operations of rough round grinding or on rough transitions of turning operation. The studied machining process can be implemented on lathes that are equipped with the additional, replaceable high-speed electric drive of rotation of a thin abrasive wheel. The use of the method of processing the outer cylindrical surfaces by thin abrasive wheels provides: the use of low cost cutting tools, reduction of the main processing time due to the greater depths of cutting, increase productivity and reduce the cost of processing and versatility of the process, due to the ability to process the cylindrical surfaces of parts that are formed from a variety of materials with significantly different physical and mechanical properties.

Multi-objective integrated scheduling optimization of semi-combined marine crankshaft structure production workshop for green manufacturing

In order to realize green manufacturing in the production process of semi-combined marine crankshaft structural parts, good job scheduling and reasonable workshop layout are the key. In traditional method, flexible job shop scheduling problem (FJSP) and the multi-row workshop layout problem (MRWLP) are regarded as separate tasks. However, the separate optimization method ignores the interaction between FJSP and MRWLP. Because the process sequencing of FJSP affects the layout results of processing machines, while the layout scheme of MRWLP affects the scheduling completion time through the transportation between processes. Therefore, it is very important to establish an integrated mathematical model for optimization of both layout and scheduling simultaneously to explore the common influence of the two resource constraints on scheduling results. At the same time, the transportation task is also a manufacturing process that cannot be ignored, which affects the completion time and energy consumption of the workshop, especially the heavy industrial manufacturing workshop with crane as transportation equipment. According to the established model, a five-segment coding including transportation information, layout information and processing information is designed, and two heuristic selection strategies are integrated into non-dominated sorting genetic algorithm II (NSGA-II) to optimize the iterative results twice. Finally, the effectiveness of the integrated mathematical model is verified by an example, which provides guidance for green manufacturing in the shipbuilding industry.