Rework Rates Research Articles

Investigations on process vibrations and forces and their effects on resulting optical component qualities in a CNC grinding process

Abstract The presented investigations deal with the real-time evaluation and recording of vibrations and forces during a CNC grinding process as well as the analysis and control of process influences on the surface quality of optical components. The experiments were performed on a 5-axis CNC machine and monitored using a laser vibrometer and a dynamometer. The subsequent examination of the component surfaces and topographies is carried out with the aid of two white light interferometry systems (macroscopic and microscopic). The aim of the investigations is to record and analyze correlations between the vibrometry, force and topography measurement data in order to examine their influence on the grinding process and the resulting component quality and to examine whether in-process vibrometry and force measurements can be used to detect and predict component quality during the process. Furthermore, the influence of individual grinding parameters on the grinding forces as well as the resulting component qualities are investigated under consideration of the surface roughness. It is shown that the vibration and force data measured during the grinding process correlate to a high degree with the recorded topography data. In addition, it was possible to determine which parameters have a significant influence on the observed CNC process. The setting parameters feed speed, tool grain size, and infeed depth had the greatest influence on the roughness and also on the forces. For example, the roughness could be reduced by around 47% by using the lowest considered feed speed compared to the highest. Furthermore, the forces were significantly influenced by the ultrasonic and could be reduced by around 53% by switching it on. The results underline the importance of real-time measurement technologies for improving CNC grinding processes, as they provide critical insights into the dynamic behavior of the system and its impact on the surface quality of optical components. This research demonstrates that by understanding the correlation between process forces, vibrations, and resulting surface topographies, it is possible to develop predictive models for in-process quality assurance. Consequently, the findings pave the way for more efficient and reliable grinding processes, reducing rework rates, and production costs. The presented approach can be directly applied in high-precision manufacturing environments, contributing to advancements in the fabrication of high-quality optical systems.

Agent-based modeling system for real-time characterization of film thickness in digital twin coating

In the automated spraying workshop of ship segments, poor visibility caused by dust and fog hampers the effectiveness of the video monitoring system. The traditional method used during the automated spraying process fails to provide real-time measurement of film thickness and prediction of spraying quality, resulting in uneven film thickness and high rework rates. Robotic spraying technology also faces challenges, such as the time-consuming and labor-intensive process of building and computing a highly reliable Computational Fluid Dynamics (CFD) based spraying film-forming simulation model, which cannot be reflected in real-time during the spraying process. The digital twin characterization method, based on the agent model, offers a solution to these limitations and challenges, providing new ideas and approaches for improving and optimizing the spray film formation model. This paper presents the development of a real-time characterization system for sprayed film thickness based on digital twin technology. The spraying film thickness under different working conditions is obtained using Ansys-Fluent simulation software by varying the gun height and gun speed. The predictive model for spraying film thickness is then established using the obtained simulation data and the corresponding gun height and gun speed, employing the surrogate modeling method (BP neural network). The real-time characterization system for spraying film thickness is developed by combining C# and Unity3D. Finally, in order to ensure the accuracy of the predictive model, a spraying experimental platform is built to verify the accuracy of the predictive model.

Fuzzy Radar Evaluation Chart for Improving Machining Quality of Components

Some studies have shown that any part machined by an outsourcer usually has several basic quality characteristics. When the outsourcer’s process capabilities are insufficient, the defective rate of various quality characteristics of the product will increase, thereby raising the rework rate and scrap rate. As a result, maintenance costs will go up, economic value will decrease, and even carbon emissions can increase during the production process. In addition, the process capability index and the radar chart are widely used in engineering management and other fields. Since process indicators often contain unknown parameters, sample data are needed for evaluation. With the rapid development of the Internet of Things and big data analysis, many companies regard rapid response as a basic requirement for timeliness and cost consideration. Therefore, companies often have to evaluate the process quality of ten small samples and decide whether to make some improvements. In order to solve the above problems, this study proposed a fuzzy radar chart evaluation model for the process quality of multi-quality characteristic parts based on the process capability index. Using this model can help all parts manufacturers continue to improve the quality of their machined parts as well as reduce their rework and scrap rates. Meanwhile, carbon emissions can be lessened during the production process, and companies can fulfill their social responsibilities. This fuzzy radar chart evaluation model is based on confidence intervals. As the company’s past experience is incorporated, the evaluation accuracy can be maintained even with a smaller sample size. Furthermore, the fuzzy radar evaluation chart can simultaneously evaluate the process capabilities of all quality characteristics of the part. In addition to making it easier for manufacturers to master all quality characteristics, quality process capability can also help them seize improvement opportunities.

From Uncertainty to Precision: Advancing Industrial Rework Rate Analysis with Fuzzy Logic

The industrial sector plays a crucial role in the global economy by providing products to meet the ever-evolving societal needs. However, the relentless pursuit of quality and efficiency faces challenges, with one of the most significant obstacles being rework. Accordingly, this paper presents the development of a rework rate index in the industrial sector, using Mamdani-type fuzzy logic as the methodology, aiming to overcome the limitations of traditional approaches and capture the complexity and uncertainty of rework data. Seventeen indicators grouped into different categories were analyzed by assessing correlations to obtain the proposed index. The results demonstrated the effectiveness of the Mamdani fuzzy logic approach in evaluating rework rates, offering comprehensive insights and clear categorizations. The analysis of correlations among indicators revealed intricate interdependencies influencing rework rates. The creation of the Rework Reduction Index signifies a significant advancement in quality and efficiency management within the industrial sector. The fuzzy approach provides a comprehensive means to address data uncertainty and subjectivity, enabling a precise and contextual evaluation of rework rates. The results have direct implications for informed decision-making, allowing companies to identify problematic areas, allocate resources efficiently, and monitor progress over time. Furthermore, the proposed approach has the potential to inspire similar practices in other companies, contributing to enhancing efficiency and quality in industrial processes Future studies could extend the application of the Rework Reduction Index to various industrial sectors and explore the relationship between index classifications and traditional performance metrics.

Multicriteria decision-making method for scheduling problem based on smart batches and their quality prediction capability

The scheduling problem in manufacturing companies with high rework rates remains a complex research area to date. This paper presents a new approach for manufacturing scheduling that combines a predictive schedule with a proactive multicriteria decision-making method based on smart batches and their quality prediction capability. Each batch embeds an algorithm that allows it to predict its quality out of the next workstation. As soon as a batch determines that its process is too hazardous, a collaborative rescheduling decision, using the analytic hierarchy process (AHP), is initiated with its peer. This article details the proposed approach along with the AHP structure and presents the considered decision problem. A simulation model inspired by a lacquering-robot case study is described to validate this proposition. Then, the results of different scenarios are presented and discussed, highlighting the impact of social myopia on smart batches.

Sensor-Enabled Multi-Robot System for Automated Welding and In-Process Ultrasonic NDE.

The growth of the automated welding sector and emerging technological requirements of Industry 4.0 have driven demand and research into intelligent sensor-enabled robotic systems. The higher production rates of automated welding have increased the need for fast, robotically deployed Non-Destructive Evaluation (NDE), replacing current time-consuming manually deployed inspection. This paper presents the development and deployment of a novel multi-robot system for automated welding and in-process NDE. Full external positional control is achieved in real time allowing for on-the-fly motion correction, based on multi-sensory input. The inspection capabilities of the system are demonstrated at three different stages of the manufacturing process: after all welding passes are complete; between individual welding passes; and during live-arc welding deposition. The specific advantages and challenges of each approach are outlined, and the defect detection capability is demonstrated through inspection of artificially induced defects. The developed system offers an early defect detection opportunity compared to current inspection methods, drastically reducing the delay between defect formation and discovery. This approach would enable in-process weld repair, leading to higher production efficiency, reduced rework rates and lower production costs.

Autonomous Stair Climbing Robot

An autonomous robot, also known as simply an autorobot or autobot, is a robot that performs behaviors or tasks with a high degree of autonomy. Autonomous robotics is usually considered to be a subfield of artificial intelligence, robotics, and information engineering. Specifically, “autonomous robots can help: Increase efficiency and productivity. Reduce error, re-work, and risk rates. Improve safety for employees in high-risk work”environments. In this COVID era every 4 out of the 5 Fortune 500 e-commerce companies and especially the e-commerce giants like Walmart , Amazon and Flipkart are focusing even more on contact less delivery. Delivery using automated bots is a concept that can be used even after the Covid situation gets over. The popularity of e-commerce buying is exploding, and the phenomenon has huge implications for shippers and distributors. To paraphrase Charles Darwin, “those companies best prepared to adapt to this new reality are the ones that will flourish while laggards will be left in the dust”. “Logistics is all about movement from one place to another. This movement happens across facilities and within facilities. While AGVs (AUTOMATED GUIDED VEHICLES) have found their way into applications of material movement inside a warehouse, they are designed to move across flat surfaces with minor undulations (in some cases requiring specialised mezzanine surfaces). This paper comes up with conceptual building and designing an autonomous robot which can work on flat surfaces and even climb up and down standard stairs with a payload of 3-5kg. This paper further will inform you about the conceptual building of an autonomous stair climbing robot involving all the steps like sensor fusion , navigation , tracking , mapping and path planning.

Optimization of inventory system with defects, rework failure and two types of errors under crisp and fuzzy approach

<p style='text-indent:20px;'>In this paper, a new approach was applied to a single-item single-source (<inline-formula><tex-math id="M1">\begin{document}$ SISS $\end{document}</tex-math></inline-formula>) system at the "<inline-formula><tex-math id="M2">\begin{document}$ EOQ-type $\end{document}</tex-math></inline-formula>" mode considering imperfect items and uncertainty environment. The mentioned method was intended to produce an optimum order/production quantity as well as taking care of imperfect processes. The imperfect proportion of the received lot size was described by an imperfect inspection process. That is, two-way inspection errors may be committed by the inspector as separate items. Thus, this survey was aimed to maximize the benefit in the traditional inventory systems. The incorporation of both defects and defective classifications (Type-<inline-formula><tex-math id="M3">\begin{document}$ I\&II $\end{document}</tex-math></inline-formula> errors) was illustrated, in a way that the defects were returned by the consumers. Moreover, this inventory model had an extra step in the scope of inspection; which occurred after the rework process with no inspection error. To get closer to the practical circumstances and to consider the uncertainty, the model was formulated in the fuzzy environment. The demand, rework, and inspection rates of the inventory system were considered as the triangular fuzzy numbers where the output factors of the inventory system were obtained via nonlinear parametric programming and Zadeh's extension principle. Finally, this scenario was illustrated through a mathematical model. The concavity of the objective function was also calculated and the total profit function was presented to clarify the solution procedure by numerical examples.</p>

Investigating morphodynamics on Little Ice Age lateral moraines in the Italian Alps using archival aerial photogrammetry and airborne LiDAR data

The rapid glacier recession in the European Alps exposes large amounts of unconsolidated sediment. Several processes are involved in the reworking of this sediment on steep lateral moraines, e.g. small slides on the upper slopes, sheet erosion by snow gliding, fluvial erosion and debris flows. To gain deeper insight into the dependence of the morphodynamics on lateral moraines on the time since deglaciation, we analysed erosion rates and geomorphological processes occurring at different distances from the present-day glacier termini. Moreover, we assessed the significance of parameters like slope gradient, altitude a.s.l. and the presence of dead ice for the morphodynamics. We used historical (1959) as well as contemporary (2016) aerial images and airborne laserscanning data (2006) to derive orthophotos, 3D point clouds (SfM) and Digital Elevation Models of Difference (DoD). These models cover the entire lateral moraine sections of two glaciers in South Tyrol, Italy, but detailed analysis was restricted to five test areas which deglaciated at different times. We were able to detect areas with decreasing geomorphological activity showing an erosion rate below 1 cm per year mainly on moraine sections remote from the contemporary glacier tongue. Simultaneously, moraine sections with continuous high levels of morphodynamics or even increasing activity were observed. The latter show heavy gullying on the upper slopes with erosion rates of 5.9–10.1 cm per year and no indications of decreasing rework rates could be found. We suppose a strong influence of degrading debris-covered dead ice, which all these slope experienced over many years after glacier melting. However, moisture availability and the slope angles, amongst others, also affect the geomorphological processes forming the moraine slopes. Thus, our results are only partly consistent with the literature, because we found areas with decreasing activity, as assumed in the paraglacial adjustment model, as well as moraine sections where no stabilization can be observed to date.

Production data analysis system using novel process capability indices-based circular economy

PurposeThe purpose of this paper is to establish mechanisms for process improvement so that production efficiency and product quality can be expected, and create a sustainable development in terms of circular economy.Design/methodology/approachThe authors obtain a critical value from statistical hypothesis testing, and thereby construct a process capability indices chart, which both lowers the chance of quality level misjudgment caused by sampling error and provides reference for the processes improvement in poor quality levels. The authors used the bottom bracket of bicycles as an example to demonstrate the model and methods proposed in this study.FindingsThis approach enables us to plot multiple quality characteristics, despite varying attributes and specifications, onto the same process capability analysis chart. And it therefore increases accuracy and precision to reduce rework and scrap rates (reduce), increase product availability, reduce maintenance frequency and increase reuse (reuse), increase the recycle rates of components (recycle) and lengthen service life, which will delay recovery time (recovery).Originality/valueParts manufacturers in the industry chain can upload their production data to the cloud platform. The quality control center of the bicycle manufacturer can utilized the production data analysis model to identify critical-to-quality characteristics. The platform also offers reference for improvement and adds the improvement achievements and experience to its knowledge management to provide the entire industry chain. Feedback is also given to the R&D department of the bicycle manufacturer as reference for more robust product designs, more reasonable tolerance designs, and selection criteria for better parts suppliers, thereby forming an intelligent manufacturing loop system.

Economic production quantity in an imperfect manufacturing process with synchronous and asynchronous flexible rework rates

We present inventory models to schedule an imperfect manufacturing process where a proportion of the items are defective. The proportion is known; and the production is followed by a 100% inspection. The manufacturer implements a rework strategy to rectify the defective items. Since the rework can be implemented on a number of plans, a flexible rework rate is presented. The flexible rework offers the manufacturer the selection of the rework rate, which can be different from the production rate, and also the selection of the rework process itself, which can be asynchronous and synchronous. Under the asynchronous rework, the defective items are kept until the completion of the production lot; while, under the synchronous rework, the defective items are reworked as soon as they are produced. A linear rework cost function of the rework rate is assumed. The objective of this paper is to develop mathematical models to determine the optimal lot sizes and backorders for different assumptions about the rework rate and the rework process. It has been proven that the rework strategy and the rework rate influence the lot size and the backorder, especially for large values of the defective proportion.

Heterogeneous recurrence monitoring of dynamic transients in ultraprecision machining processes

In situ monitoring and control of process variations are important for quality assurance in ultraprecision machining (UPM) processes. Recent advancements in sensing and communication technology have fueled increasing interests to develop sensor-based monitoring approaches for anomaly detection in the UPM process. However, conventional approaches are limited in their ability to address the complex dynamics hidden in the nonlinear and nonstationary processes. As a result, it is difficult for them to effectively capture the process variations of UPM. This paper presents a new heterogeneous recurrence monitoring approach to detect dynamic transients in UPM processes. First, a high-dimensional state space is reconstructed from in situ sensing signals. A Dirichlet process (DP) driven clustering approach is then developed to automatically segment the state space into local recurrence regions. Furthermore, a fractal representation is designed to characterize state transitions among recurrence regions and extract novel measures to quantify heterogeneous recurrence patterns. Finally, we integrate a multivariate control chart with heterogeneous recurrence features for in situ monitoring and predictive control of the UPM process. Experimental results showed that the proposed approach effectively detects transitions with a small magnitude, i.e., ρ=28 to ρ=27 in the Lorenz system, and identifies the shift from stable cutting (Ra=35nm) to unstable cutting (Ra=82nm) in UPM processes with an average run length of 1.0. This paper presents a novel data-driven DP clustering approach to characterize heterogeneous recurrence variations and link with the quality of surface finishes in UPM processes. This new DP recurrence approach circumvents the need to empirically define local recurrence regions and is shown to have strong potentials for manufacturing process monitoring and control that will increase the surface integrity and reduce rework rates.

P101 How to do more with less in the molecular HLA laboratory?

Aim Providing molecular HLA services with increased volumes and no additional staff, while maintaining or improving the quality of output. Methods A contracted LEAN consultant created an in-house team to study the molecular HLA lab workflow, consisting of evaluating sample volumes, error rates, and staffing levels. The team then implemented the following: Phase one was to cross train staff to perform all lab functions as cross training was viewed to offer flexibility in all aspects of the workload and process. Phase two was to determine the most efficient workflow. Standard Work, Single-Piece-Flow, along with standard batches versus Right-Size-Batches were studied to evaluate the efficacy of each. Phase three studied the error rates and re-work rates for all processes to determine root cause of errors, to include evaluating staff errors and the need for automation and/or upgrading technology. Phase four consisted of the design of a visual, posted Production Board, to include process timing, task assignments, and daily metrics including sample volumes and individual and collective staff output. Results Even as the volumes continue to increase, the implementation of the changes resulting from the points above have shown a substantial impact, including: Error rate reductions. For example, the decrease in the pre-analytical error rate from 7.9% to 3.2%. Turn-Around-Time (TAT) reductions. For example, the TAT for Chimerism testing has decreased by half, even as the volume has increased by almost 300%. Increased cross training. Allows for greater flow of ideas on efficiency and cooperation in response to higher volumes. Increased team work and staff morale. Better communication via the production board has increased job satisfaction. Improvements in automation and technology. Data gathered helped obtain new equipment and software. Improvements in services offered. Data on the bone marrow program showed that SBT would not offer the resources needed to meet our TAT goals. The decision was made to validate and implement NGS as our method of high resolution typing. Conclusions As the lab continues to grow and adjust, efficiency, staff morale, and client satisfaction continue to improve as a result of the LEAN implementations. Now, areas of concern are considerably easier to define and problem-solve.

Control of surface defects on plasma-MIG hybrid welds in cryogenic aluminum alloys

Lately, high production rate welding processes for Al alloys, which are used as LNG FPSO cargo containment system material, have been developed to overcome the limit of installation and high rework rates. In particular, plasma-metal inert gas (MIG) hybrid (PMH) welding can be used to obtain a higher deposition rate and lower porosity, while facilitating a cleaning effect by preheating and post heating the wire and the base metal. However, an asymmetric undercut and a black-colored deposit are created on the surface of PMH weld in Al alloys. For controlling the surface defect formation, the wire feeding speed and nozzle diameter in the PMH weld was investigated through arc phenomena with high-speed imaging and metallurgical analysis.

A learning curve-based method to implement multifunctional work teams in the Brazilian footwear sector

This paper presents a method for implementing multifunctional work teams in a footwear company that followed the Taylor/Ford system for decades. The suggested framework first applies a Learning Curve (LC) modeling to assess whether rotation between tasks of different complexities affects workers' learning rate and performance. Next, the Macroergonomic Work Analysis (MA) method (Guimarães, 1999, 2009) introduces multifunctional principles in work teams towards workers' training and resources improvement. When applied to a pilot line consisting of 100 workers, the intervention-reduced work related accidents in 80%, absenteeism in 45.65%, and eliminated work related musculoskeletal disorders (WMSD), medical consultations, and turnover. Further, the output rate of the multifunctional team increased average 3% compared to the production rate of the regular lines following the Taylor/Ford system (with the same shoe model being manufactured), while the rework and spoilage rates were reduced 85% and 69%, respectively.

Process Analytics, Modeling, and Optimization of an Industrial Batch Annealing Operation

Batch annealing operation of a secondary cold-rolling mill has numerous operational challenges, including processing of input coils from varied sources with high variability, pressure to maintain low inventory level and lack of process model for customized cycle design for individual stacks. The present work describes a case study of a modern tinplate manufacturing operation, where hot-rolled steel coils are cold rolled to very thin sheet thickness, followed by batch annealing and tinplating operation. It was envisaged that further stringent quality specifications in mechanical properties (e.g., hardness variations across the coil) will result in high rework and down-gradation rates. By combining the process analytics results with process model (phenomenological and neural-network) simulations, three types of recommendations were made during the present work: (a) a~new classification of coils for stacking, (b) a new chemistry specifications for input coils, and (c) a new model-based process cycles (temperature and soaking time) for the various coil classes. This integrated approach has resulted in overall rejection and down-gradation rates for two major products by 44% and 60%, thereby enabling the envisaged tightening of quality specifications. The achieved benefits have been monitored and sustained for over one year.

On the optimal selection of process alternatives in a Six Sigma implementation

Six Sigma is at the top of the agenda for many companies that try to reduce cost and improve productivity. Many of the top manufacturing companies implement thousands of Six Sigma projects every year and this implementation demands a significant investment of capital that requires a careful analysis to make sure that the benefits obtained are much higher than the actual investment. This cost benefit analysis is crucial, especially for companies whose products have a small profit margin. In this paper, two optimization models that will assist management to choose process improvement opportunities are presented. These models consider a multi-stage, asynchronous manufacturing process with the opportunity to improve quality (scrap and rework rates) at each of the stages. The first model is to maximizing the sigma quality level of a process under cost constraint while the selection of Six Sigma alternatives to maximize process returns is considered by the second model. Process quality improvement usually results in costs associated with the purchase of new technology, modification of existing equipment, training employees, hiring new employees and investment in information technology infrastructure. The proposed models recognize that a company competes for funds and that benefits can result in either improved revenue or reduction in costs. An example illustrates the application of the optimization models developed and results show that in some scenarios implementing Six Sigma may not be financially beneficial.

The effects of rework on the shopfloor control in wafer fabrication

The purpose of this paper is to study the effect of rework operations on the shopfloor control’s strategies, including order release and dispatching. An attempt is made to determine the performance of various production control strategies on the system performance indicators under different levels of rework rate. Also the interaction of order release and dispatching strategies under different rework operations is investigated. Some representative shopfloor control (SFC) strategies are considered in our simulation model. It was found that the effect of rework operation on the system performance is significant. The order release and dispatching strategies’ performance is affected by the rework operation. The performance is improved dramatically if a suitable combination of order release and dispatching strategies is adopted. Under different rework rates and performance indicators a suitable combination of SFC strategies is suggested in this paper.

Effect of refractory phase separation on investment mould integrity

AbstractT he casting of liquid metals to produce solid objects is a manufacturing process which has been practised for over five thousand years, with investment casting being one of the oldest known metal shaping methods. The technique itself has tremendous advantages in the production of quality components and key benefits of accuracy, versatility, and integrity. As a result, the process is one of the most economic methods of forming a wide range of metal components. The mechanical performance of an investment mould directly influences the quality, tolerance, re-work, and scrap rates of castings. The ceramic consists of a mixture of phases, which interact with each other during firing to form a bonded structure. The extent of this interaction and the properties of the resultant bonding phase are influenced by the purity of the raw materials. Specialist X-ray analysis techniques allow both quantitative and qualitative elemental compositions of ceramic materials to be determined. This was used effectively ...

Cycle-time improvements for photolithography process in semiconductor manufacturing

Cycle-time reduction is of great importance to semiconductor manufacturers. Photolithography, being one of the most repeated processes, is an area where substantial improvements can be made. We investigate the effects of various process control mechanisms for photolithography on the cycle-time at the process and at the overall fab via a simulation study. Test run policy at the photolithography station, test run frequency, duration of inspection, and machine dedication policy for the equipment are the factors we consider. Equipment down time due to preventive or breakdown maintenance and rework rates are also taken into account. Parallel testing, where test wafer is inspected while the lot is being processed, is the best policy in terms of cycle-time performance. Long inspection time and infrequent, long down times have the most adverse effects, but flexible machine assignment may reduce the impact of down times. Test run frequency is only significant for serial testing, where processing of the lot is not finished until the failed test wafer is stripped and reworked.