Manufacturing Letters最新文献

{"title":"Production overrun optimization considering supply chain network reliability","authors":"Dawei Xue ,&nbsp;Xi Gu ,&nbsp;Hae Chang Gea","doi":"10.1016/j.mfglet.2024.09.026","DOIUrl":"10.1016/j.mfglet.2024.09.026","url":null,"abstract":"<div><div>Production overrun is a common practice in manufacturing to meet the demand by increasing the number of qualified products and compensating for manufacturing defects. While production overrun can improve Supply Chain Network Reliability (SCNR), it leads to higher material costs. In this paper, a model is proposed to evaluate SCNR by incorporating the reliabilities of inbound logistics, operations, and outbound logistics. Based on the proposed SCNR model, we study the optimal production overrun of each manufacturing site in a supply chain network and identify the production plan that satisfies the reliability requirement with minimum total production overrun penalty. By analyzing the monotonicity of the objective and constraint functions of the formulated problem, an algorithm based on linearization is developed to solve this optimization problem. Numerical examples across various scales are presented to illustrate the developed model and method. The impact of the penalty coefficient of the production overrun on the result is investigated. The results from the numerical examples provide managerial insights on allocating resources in the entire supply chain network and improving the supply chain reliability and competitiveness.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"41 ","pages":"Pages 219-228"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A review of ice cream manufacturing process and system improvement strategies","authors":"Asmaa Harfoush ,&nbsp;Zhaoyan Fan ,&nbsp;Lisbeth Goddik ,&nbsp;Karl R. Haapala","doi":"10.1016/j.mfglet.2024.09.021","DOIUrl":"10.1016/j.mfglet.2024.09.021","url":null,"abstract":"<div><div>The food industry faces several challenges, including intricate supply chains, compliance with food safety regulations, sustainability concerns, and the rising demand for high-quality products. Furthermore, consumers increasingly seek personalized food products with specific fat, sugar, and micronutrient levels. The ice cream industry is no exception in facing these challenges. Fortunately, Industry 4.0 technologies, such as smart manufacturing, data analytics, and the Industrial Internet of Things (IIoT), offer viable solutions to many of the aforementioned challenges. However, a deeper understanding of industrial ice cream manufacturing processes and systems is essential to apply these technologies effectively. While the related literature has often focused on ingredient selection to achieve the desired ice cream flavor and texture, there is a noticeable absence of comprehensive efforts to evaluate the impact of process- and systems-related aspects in ice cream manufacturing. This study employs a semi-systematic literature review approach to compile recent research that examines the influence of process- and system-level factors on ice cream product quality and production processes, focusing on the aspects that can benefit from implementing Industry 4.0 technologies. The literature review reveals that 1) at the process level, researchers have focused on three key processes (i.e., pasteurization, homogenization, and dynamic freezing) and their impact on the quality of the ice cream; 2) at the system level, researchers have concentrated their efforts on techno-economic factors, process scheduling, productivity, and sustainability.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"41 ","pages":"Pages 170-181"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fusion IK: Solving inverse kinematics using a hybridized deep learning and evolutionary approach","authors":"Steven Rice ,&nbsp;Ahmed Azab ,&nbsp;Sherif Saad","doi":"10.1016/j.mfglet.2024.09.005","DOIUrl":"10.1016/j.mfglet.2024.09.005","url":null,"abstract":"<div><div>Inverse kinematics is a core aspect of robot manipulation. This paper presents an approach to solving Inverse Kinematics (IK) for robots, including articulated industrial ones, combining deep learning with an evolutionary algorithm. Fusion IK passes the manipulator’s target and current joint values into a neural network, the results of which are then used to seed an evolutionary algorithm, Bio IK, to complete the solution of the inverse kinematics problem. Fusion IK allows for solving the position and orientation of the robot while attempting to minimize joint movement times. Comparisons between Fusion IK and its underlying algorithm Bio IK are tested on a six-degree-of-freedom articulated industrial robot as well as a 20-degree-of-freedom robot to explore the move times that Fusion IK produces. The comparisons show that the variations of the Fusion IK algorithm show comparable results to its underlying evolutionary Bio IK algorithm on a six-degrees-of-freedom articulated robot and improvements on a 20-degree-of-freedom robot without any additional hyperparameter tuning. The results show that Fusion IK could be of real value regarding the movement time and the quality of the obtained solutions upon further research, especially with higher degree-of-freedom robots.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"41 ","pages":"Pages 9-18"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An unconstrained and non-redundant identification method of geometric errors and compensation of machine tools by X-AX Laserbar","authors":"Yukun Xiao ,&nbsp;Guangyan Ge ,&nbsp;Ming Deng ,&nbsp;Jun Lv ,&nbsp;Zhengchun Du","doi":"10.1016/j.mfglet.2024.09.007","DOIUrl":"10.1016/j.mfglet.2024.09.007","url":null,"abstract":"<div><div>Efficient and accurate measurement and identification of geometric errors are crucial for improving the precision of CNC machine tools. The X-AX Laserbar, as a novel tool for indirect measurement, has not been extensively studied for the identification of geometric errors in machine tools. In this paper, the geometric error model for a three-axis machine tool is established to illustrate the multilateration measurement principle of the laserbar, and a non-redundant and unconstrained identification method is proposed to identify these geometric errors. This method avoids the use of redundant parameters and additional constraints by employing pose error twists to describe the geometric errors. These pose error twists are identified in a transitional coordinate system, and then the geometric errors will be identified in the machine coordinate system by deriving the relationship between the pose errors and geometric errors. The proposed method is validated with the VMC-850E three-axis machine tool. The geometric error measurement using a laserbar is completed in about 40 min, showing great efficiency. The experimental results indicate that the proposed method is capable of accurately identifying the 17 geometric errors required for error compensation. The identified geometric errors are then applied to the machine tool’s accuracy improvement through error compensation. The results show that the actual geometric errors are controlled to a low level. The proposed method can efficiently measure the geometric errors of three-axis machine tools and contribute significantly to improving their geometric accuracy.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"41 ","pages":"Pages 31-42"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Model-based tool wear detection and fault diagnosis for end mill in various cutting conditions","authors":"Jun-Young Oh,&nbsp;Jae-Eun Kim,&nbsp;Wonkyun Lee","doi":"10.1016/j.mfglet.2024.09.076","DOIUrl":"10.1016/j.mfglet.2024.09.076","url":null,"abstract":"<div><div>In recent developments in the field of manufacturing systems, there has been a growing emphasis on optimizing cutting conditions. These optimizations are primarily based on intricate parameters, such as the material removal rate (MRR), surface roughness, and position accuracy. Simultaneously, there’s an increasing focus on enhancing manufacturing efficiency through equipment maintenance strategies that consider parameters, such as corrosion, pressure, temperature, vibration, and other environmental factors. Wear is inevitable during processing, which affects productivity. It is generated in various forms, such as flank, crater, and edge wear, which reduce the tool lifespan and impact machining quality, especially by increasing the cutting forces. Various studies have been conducted to address this issue. Direct measurements using microscopes have high accuracy but require interruption during the process, which adversely affects efficiency and productivity. As a solution, the modern era has witnessed an increase in indirect methods. These methods are often sensor-based, capture data during the machining process, and employ various models, including emerging artificial intelligence techniques, for predicting tool wear. However, these methods have problems with environmental susceptibility, reduced reliability, limitations of application, and excessive costs. This paper suggests a tool wear integrated cutting load prediction model, tool wear detection, and fault diagnosis mechanism. The tool-wear-integrated cutting-load prediction model was constructed by combining the cutting-load prediction and tool-wear models. The coefficients of the model were derived from the actual cutting data extracted by the spindle load. Tool wear detection was implemented by dividing regions based on the tendency of the coefficient of the constructed tool wear integrated cutting load prediction model and the errors between the predicted and actual values. The proposed model demonstrated a performance comparable to that of the existing models in a single-cutting-condition path. However, it excelled in extracting the tool wear coefficients in paths with a mixture of various cutting conditions, which was not achievable with conventional models. Based on these coefficients, the cutting force was predicted with a maximum error of 3.3 %. Also, an accurate determination of the tool-wear regions was possible. Furthermore, the performance of the tool fault diagnosis method was validated using images of tools identified as being at risk of damage.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"41 ","pages":"Pages 595-604"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental validation of the amplitude ratio as a metric for milling stability identification","authors":"Mark A. Rubeo","doi":"10.1016/j.mfglet.2024.09.078","DOIUrl":"10.1016/j.mfglet.2024.09.078","url":null,"abstract":"<div><div>This paper presents the experimental validation of the amplitude ratio, a metric for milling stability identification. The amplitude ratio quantifies the severity of chatter by comparing the amplitude of the expected frequency content of a milling signal (i.e., tooth passing frequency, runout frequency, and harmonics) to the amplitude of the chatter frequency, if present. Through multiple iterations of a milling time domain simulation, the amplitude ratio diagram, which characterizes stable and unstable milling behavior over a range of spindle speeds and axial depths of cut, may be generated. In this paper, a comparison of the simulated and measured amplitude ratios for a series of milling test cuts is presented. It is shown that the amplitude ratio is suitable for identifying milling stability in both simulations and experiments. Additionally, it is shown that through judicious selection of low-cost sensors, implementation of the amplitude ratio is cost efficient. Direct comparison of the simulated and measured amplitude ratios demonstrates the effectiveness of the approach.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"41 ","pages":"Pages 610-618"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Femtosecond laser joining of Stellite and stainless steel","authors":"David Fieser ,&nbsp;Lingyue Zhang ,&nbsp;Matthew Yao ,&nbsp;Hugh Shortt ,&nbsp;Peter Liaw ,&nbsp;Anming Hu","doi":"10.1016/j.mfglet.2024.09.039","DOIUrl":"10.1016/j.mfglet.2024.09.039","url":null,"abstract":"<div><div>This research explores the practicality of fusing Stellite 6, a cobalt-chromium alloy known for its high performance, with stainless steel, utilizing various laser welding approaches. The primary challenge addressed is the joining of dissimilar materials, which presents obstacles such as divergent melting points and disparate coefficients of thermal expansion. The aim is to achieve a metallurgical bond between Stellite and stainless steel that retains desirable properties. The study employs both continuous wave and femtosecond laser welding techniques, subjecting the resultant joints to rigorous analysis to assess their impact on the properties of the bond. Initial tensile testing delineated the intrinsic mechanical characteristics of the materials, revealing that while Stellite exhibits a lower ultimate tensile strength, it compensates with greater elongation compared to stainless steel. The use of continuous wave laser welding proved to be capable of creating the bond; however, it also precipitated a considerable decline in the tensile strength of the Stellite component as a result of the thermal processing involved. In contrast, femtosecond laser welding emerged as a more effective method, enhancing the joint’s overall strength and ductility. This improvement is attributed to the femtosecond laser’s precise control over thermal exposure, which confines the heat to the intended weld zone, thereby safeguarding the adjacent material from damage. Further insights were gleaned from Scanning Electron Microscopy, which showed a preferable intergranular fracture in samples welded with the femtosecond laser—a feature typically associated with ductile failure modes. The femtosecond laser welding approach culminated in a joint efficiency of 53.7%, mirroring the innate yield strength of the Stellite wire. This outcome suggests that such welded joints possess the requisite robustness for practical deployment, thus underscoring the potential of femtosecond laser welding in applications requiring the joining of Stellite to stainless steel.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"41 ","pages":"Pages 332-338"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a wireless smart sensor system and case study on lifting risk assessment","authors":"Vignesh Selvaraj ,&nbsp;Aditya Nagaraj ,&nbsp;Benjamin Gregory Whiffen,&nbsp;Sangkee Min","doi":"10.1016/j.mfglet.2024.09.027","DOIUrl":"10.1016/j.mfglet.2024.09.027","url":null,"abstract":"<div><div>With the widespread adoption of Industry 4.0 and smart manufacturing concepts across industries, sensor development, system integration, and data analysis have become important aspects of efficient manufacturing operations. In addition to monitoring the performance of machines, significant importance is given to human condition monitoring in factories, using body-worn sensors to ensure the well-being of workers and for injury prevention. This research presents the development of a body-worn sensor system capable of sampling acceleration and rotation data up to 400 Hz and wirelessly transmitting the data over Bluetooth Low Energy (BLE). Further, the communication protocols for data acquisition, data communication within the device, Real Time Operating System (RTOS) programming, and multi-threading are described. This system is designed in such a way that multiple devices can be connected to the Data acquisition (DAQ) system simultaneously, and data is collected from the sensors in a synchronized manner. This information is valuable for the wider adoption of sensor systems for human condition monitoring in industry. Lastly, to test the system’s capabilities, a case study of lifting risk assessment is presented, where data collected from the accelerometer and gyroscope are used to determine a relative estimate of the physical stress associated with a manual lifting task by using different machine learning (ML) algorithms. The case study highlights how sensor placement, feature extraction, and sensor types influence machine learning models. As the sensor system can perform computations on the edge, a framework to carry out real-time lifting risk assessment using lightweight algorithms and the most important data features is proposed.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"41 ","pages":"Pages 229-240"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Framework for LLM applications in manufacturing","authors":"Cristian I. Garcia,&nbsp;Marcus A. DiBattista,&nbsp;Tomás A. Letelier,&nbsp;Hunter D. Halloran,&nbsp;Jaime A. Camelio","doi":"10.1016/j.mfglet.2024.09.030","DOIUrl":"10.1016/j.mfglet.2024.09.030","url":null,"abstract":"<div><div>In the era of Industry 4.0, the proliferation of data within manufacturing environments has presented both unprecedented opportunities and challenges. This paper introduces a framework that capitalizes on the capabilities of Large Language Models (LLMs) to revolutionize data integration and decision-making processes in manufacturing systems. Addressing the critical need for efficient data management, our framework streamlines the consolidation, processing, and generation of responses to essential inquiries, thus enhancing manufacturers’ capabilities to extract valuable insights. The focus of this paper is twofold. First to establish a framework for the use of LLM applications in manufacturing settings. Secondly, to provide an overview of the manufacturing connection between data, AI, and chat-bots, while also addressing a few pain points identified from the manufacturing literature. The paper then introduces FILLIS (<em>Factory Integrated Logic and Language Interface System</em>), a Large Language Model assistant, through a compelling case study. FILLIS showcases remarkable versatility, excelling in tasks ranging from elucidating machine operations to language translation. The study underscores FILLIS’s proficiency in handling specific contexts, answering questions from uploaded documents with precision. However, inherent limitations surface in tasks involving mathematical operations, emphasizing the need for external agents in specific scenarios. This pivotal opportunity is explored in the proposed framework as it advocates for integrating external agents alongside LLMs, creating a more versatile and comprehensive assistant tool. The findings of this paper and proposed framework position LLMs as transformative tools for intelligent data processing.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"41 ","pages":"Pages 253-263"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Iterative correction of robotic grinding using spatial feedback for precision applications","authors":"Philip A. Olubodun,&nbsp;Joseph D. Fischer,&nbsp;Douglas A. Bristow","doi":"10.1016/j.mfglet.2024.09.031","DOIUrl":"10.1016/j.mfglet.2024.09.031","url":null,"abstract":"<div><div>Since the advent of robots, many tasks that were originally performed by humans have now been tasked to industrial robots. From a manufacturing standpoint, robots have primarily been used in pick-and-place or other non-machining operations that require high repeatability. However, with the increasing availability of CAD/CAM software and the development of high-precision metrology, comes the opportunity to integrate robots into a wider variety of manufacturing processes through the use of feedback control. One such machining operation that is being explored is precision grinding of metal parts. Most other work in this area has focused on force regulation to improve grind quality; however, this paper takes a different approach. In this work, an Iterative Learning Control (ILC) algorithm is implemented to correct the geometric error directly by altering the toolpath trajectory. Specifically, in this framework, a conservative initial cutting trajectory is implemented using a 6-DoF robotic grinding system, and the resulting part geometry is measured via a high-precision laser scanner. Based on the resultant geometric error, the toolpath is corrected and then rerun on the part. This process is then repeated iteratively until sufficient accuracy is achieved. Due to the inability to replace material in overground regions, the controller is designed with an emphasis on reducing overshoot which cannot be corrected. The controller is experimentally validated by grinding an elliptical pocket which meets FAA specifications for corrosion removal in aircraft. The results showed that within seven iterations the entire error surface could be brought to a tolerance of ±0.150 mm for the given geometry.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"41 ","pages":"Pages 264-269"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}