A study of improving overlay accuracy by applying a new outlier handling method in FPD manufacturing

As the pixel size of display devices has been reduced, overlay accuracy between layers needs to be more improved in flat panel display (FPD) manufacturing. However, because of large substrate size and non-uniform processes in FPD manufacturing, an improvement of overlay accuracy has been a challenging work. As an effort to improve overlay accuracy, overlay error correction, which is a kind of feedback control similar to one in semiconductor manufacturing, has also been applied in the photo lithography processes for FPD. However, its characteristics and problems were not technically well investigated as much as in semiconductor manufacturing. This paper investigates one of the problems encountered in the practice of the overlay error correction: outliers in the measurement of overlay errors. Such outliers can cause undesirable effects on overlay accuracy, if used for the overlay error correction. In order to systematically cope with such outliers, a new framework is proposed for detecting and handling outliers as well as for verifying the result. In the consideration of the proposed framework, a new outlier detecting and handling method is also proposed. This method is based on a robust regression technique and is compared with others through simulation to confirm its better performance.     

Human factors and ergonomics in manufacturing in the industry 4.0 context – A scoping review

Industry 4.0 revolution has brought rapid technological growth and development in manufacturing industries. Technological development enables efficient manufacturing processes and brings changes in human work, which may cause new threats to employee well-being and challenge their existing skills and knowledge. Human factors and ergonomics (HF/E) is a scientific discipline to optimize simultaneously overall system performance and human well-being in different work contexts. The aim of this scoping review is to describe the state-of-the-art of the HF/E research related to the industry 4.0 context in manufacturing. A systematic search found 336 research articles, of which 37 were analysed utilizing a human-centric work system framework presented in the HF/E literature. Challenges related to technological development were analysed in micro- and macroergonomics work system frameworks. Based on the review we frame characteristics of an organisation level maturity model to optimize overall sociotechnical work system performance in the context of rapid technological development in manufacturing industries.     

Linear and Integer Programming

Coordinate sensing systems have been widely used in various manufacturing processes to monitor product quality and automatically identify process faults. They play a crucial role in manufacturing quality improvement. For complex manufacturing processes, especially processes with multiple stages, typically not all process faults can be uniquely identified by a feasible sensing system. For these complex processes, a diagnosability study is an important issue for the evaluation and usage of coordinate sensing systems. This article conducts a diagnosability study of coordinate sensing systems based on matroid theory. The use of matroid theory improves understanding of existing results on diagnosability. In addition, new results and more efficient algorithms related to diagnosability study are investigated based on matroid theory. The developed theory and algorithms, which can be applied in a broad class of diagnosis problems, are demonstrated using a panel assembly process.     

A statistical approach to real-time quality control

Modern manufacturing processes characterized by short series, complex part geometry and high refinement values often demonstrate conditions when traditional quality control (QC) methods do not work properly. This paper presents a prototype system for real-time QC where the developed methods and applications are integrated and post-process quality control is applied only as a complement and for reference measurements. All activities are supervised and fed with information from a developed active data acquisition system. The proposed concept contributes to bridging the gap between traditional post-process control and realtime QC of machining processes.     

Product data quality validation system for product development processes in high-tech industry

Among various product data, 3D CAD data plays a key role in current product design and manufacturing processes including industrial design, detail design, CAE, inspection, mould-making, production, and so on. If 3D CAD data has geometrical or topological errors by user mistakes or modelling software bugs and those errors are not cleaned by the data creator in an early stage, the data will be transferred to the downstream operators and they have to fix the errors before starting their own work. Because 3D data is quite complex, it is very difficult to recognise the data errors manually in a modelling system before a big problem is encountered which blocks the next operation. In this case, it generally causes time delay and high cost for data correction and the effect will be bigger when the process is close to the back-end. In this research, we develop a fully automated product data quality validation and management system to support the product development processes of high-tech products like televisions, camcorders, mobile telephones, home appliances, etc. The system automatically validates the 3D data in real time and gives 3D error reports to the creator to correct modelling failures in their steps. Also, project managers can check or control the data delivery based on the data quality for each step.     

基于梯度降温的叠层制备热残余应力

针对叠层制备工艺的热残余问题,为消除传统的基于同步降温假设的理论解与实际热残余现象的差异,本文在充分考虑成形过程中沿长度和厚度方向形成的温度梯度的基础上,分别建立在层平面和厚度方向引起的热残余变形和应力的解析解,并根据不同叠层制备工艺,将降温梯度概括为同步降温、均等梯度降温、非均等梯度降温、瞬态降温的4种模式.算例表明,梯度降温会造成在层平面和厚度方向均产生热残余现象.讨论了4种梯度降温模式对热残余程度的影响,梯度越大影响越大;合理解释了同一种材料制备的工件也会因降温梯度而产生明显的弯曲变形;对于梯度材料,叠层制备顺序会显著影响热残余的程度.研究表明,梯度降温假设符合实际制备、工艺,更准确地揭示了叠层制备热残余现象产生的机理,优化制备工艺缩小降温梯度是解决热残余问题的有效途径.     

Fuzzy-based risk priority number in FMEA for semiconductor wafer processes

Semiconductor wafer manufacturing processes are considered to be complex and require considerable manpower and financial investment. Effective control to promote wafer yield is thus a very important issue. Many computational problems in traditional failure mode approaches, such as variable selection and data collection, are far too dependent on the experience of engineers, with a lack of specifically quantified values. Therefore, there are significant differences between the results of research and the actual processes. Although several researchers have revised the failure mode computation, the occurrence results continue to differ from the actual quantified values. The potential failure mode in semiconductor wafer manufacturing processes is effectively discussed using linguistic fuzzy variables to replace the severity and detection in the failure mode for re-calculation and sorting, along with the occurrence acquired from the wafer processes yield change. Based on the results of engineering experiments, the use of a risk priority number can effectively overcome the problem of a lack of objectivity in the traditional failure mode and effect analysis, as well as accurately distinguish the priority of the key failure factors so that the research results become more complete.     

Data Analytics and Machine Learning for Smart Process Manufacturing: Recent Advances and Perspectives in the Big Data Era

Safe, efficient, and sustainable operations and control are primary objectives in industrial manufacturing processes. State-of-the-art technologies heavily rely on human intervention, thereby showing apparent limitations in practice. The burgeoning era of big data is influencing the process industries tremendously, providing unprecedented opportunities to achieve smart manufacturing. This kind of manufacturing requires machines to not only be capable of relieving humans from intensive physical work, but also be effective in taking on intellectual labor and even producing innovations on their own. To attain this goal, data analytics and machine learning are indispensable. In this paper, we review recent advances in data analytics and machine learning applied to the monitoring, control, and optimization of industrial processes, paying particular attention to the interpretability and functionality of machine learning models. By analyzing the gap between practical requirements and the current research status, promising future research directions are identified.     

Mitigating forecast errors by lot-sizing rules in ERP-controlled manufacturing systems

As enterprise resource planning (ERP) becomes the dominant management software in manufacturing and distribution systems in various industries, some problems associated with its origin, material requirements planning (MRP), still need to be resolved. We examine the effect of forecasting errors, one of the common operational problems in any business operation, in the context of an ERP-controlled manufacturing system. We consider a mitigating remedy, the use of a lot-sizing rule, to cope with the consequences of forecasting inaccuracy without resorting to costly inventory-oriented buffers. An ERP-controlled manufacturing system is simulated to see how these lot-sizing rules mitigate the forecast errors and subsequently generate acceptable system performance. The simulation results should help ease ERP users’ fear of committing another fatal error in demand forecasts, instead encouraging them to consider proper lot-sizing rules to cope with forecast errors.     

A systems approach to photolithography process optimization in an electronics manufacturing environment

There are many complex problems in the optimization of an electronics manufacturing environment, and it is the view of the authors that these problems should not be solved and optimized in isolation, but analysed in the framework of a system. A systems approach offers an overall approach for solving problems, and optimizing the whole of the system as well as discrete subsystems. The research introduced in this paper integrates several techniques, namely: Integrated computer aided manufacturing DEFinition (IDEF), and experimental design and response surface methods for the analysis, control and optimization of electronic manufacturing processes. Electronics manufacturing includes three major processes; Printed Circuit Board (PCB) manufacturing, semiconductor device manufacturing and electronics assembly. This paper describes a novel generic systematic methodology that has been used to create a model to optimize the photolithography process in PCB manufacture. For this, photolithography has been considered as a whole system made up of several sub-systems. This is shown in the process map for PCBs that focuses on photolithography and its subprocesses. A model of the manufacturing process is then given with the results of this being validated using an industrial study. Optimized settings for processing equipment are given resulting in an increase in process yield within industry.     

Virtual fusion: a hybrid environment for improved commissioning in manufacturing systems

Efficiency and quality are major factors contributing to profits in manufacturing systems. Production downtime occurs during commissioning of a new system, adoption of new processes, system faults, or (un)planned maintenance; all of which result in reduced production and profit loss. Current techniques for evaluating change to a manufacturing system rely on simulation and modeling to verify processes, but ignore the physical interactions of the work parts on the system. Implementation techniques to evaluate commissioning focus on identifying issues with the cyber interfaces, ignoring the physical interfaces. To validate the cyber and physical interfaces simultaneously, physical work are sent through the system, resulting in significant costs from scrapped work parts and loss of production time. This research proposes a virtual fusion environment where the physical interfaces between a virtual work part and a manufacturing system can be investigated in real-time, on the physical system, without the expenses associated with physical work parts. The virtual environment includes a virtual fusion filter to monitor discrepancies between the physical and virtual systems, and generate a hybrid virtual-physical input signal to the system level controller for virtualisation of a work part onto a physical system. Experimental demonstrations validate the feasibility of the proposed approach.     

Simple Estimates for the Effects of Mid-spatial-Frequency Surface Errors on Image Quality

Mid-spatial-frequency surface errors can be introduced by various manufacturing processes. These errors bridge the gap between traditional figure and finish errors. Although the effects of mid-spatial-frequency errors on the imagery of an optical system can be modeled with a ray-based approach, simply tracing rays provides little insight. We present an alternative method that treats surface errors as perturbations to the nominal surface profile. This approach, combined with standard statistical methods, allows one to make simple back-of-the-envelope predictions of the effects of mid-spatial-frequency errors for various measures of optical performance. Two examples illustrating the effectiveness of this approach are presented.     

Automated manufacturability assessment of rotational parts by grinding

Automated manufacturability assessment of a given design is a key requirement in realizing complete integration of design (CAD) and manufacturing (CAM). The paper deals with a system developed for automated manufacturability assessment by machining processes. The purpose of this system is to assist designers in their effort to come up with manufacturable parts economising in terms of cost and time. Unlike most of the work done in the past, which concentrates on assessment by primary machining processes such as turning and milling, the present work deals with grinding operation. The present system uses geometric reasoning to extract manufacturing specific information from a part model. It uses a knowledge base consisting of grinding process knowledge and control rules, which are activated by the designer. It also has a provision to account for company-specific manufacturing resources to come up with meaningful assessment for part manufacturability. The use of the proposed system is demonstrated for the assessment of axisymmetric parts to be manufactured by cylindrical and internal grinding processes.     

Enhancement of accuracy of multi-axis machine tools through error measurement and compensation of errors using laser interferometry technique

The present era is witnessing advancement in digital electronics and microprocessor which enables manufacturing sector capable to produce complex components within small tolerance zone in the tune of nanometre and at one machining center. All motion control systems have some form of position feed back system fitted with the machine. Such systems are not generally accurate due to the errors in the positioning performance of the machine tool which will change over time to time due to wear, damage and environmental effects. The complex structure of multi-axis CNC machine tools produce an inaccuracy at the tool tip caused by kinematic parameter deviations resulting in manufacturing errors, assembly errors or quasi-static errors. Analysis of these errors using a laser measurement system provides the manufacturers a way to achieve better accuracy and hence higher quality output from these processes. In this communication, techniques to measure the linear positional errors of axes of CNC machine tools by a laser interferometer calibration system and accuracy enhancement using the data obtained from the calibration cycle by feeding into the machine’s controller with the help of linear error compensation package are discussed.     

Total quality control for a surface mount technology process for the manufacture of printed circuit board assemblies

Surface mount technology is used widely nowadays in the manufacture of printed circuit board assemblies in the electronics industry. The occurrence of defective products when this technology is used is mostly caused by technological problems, but sometimes it is also caused by management problems or human errors. When technological problems are being tackled, human interactions will always be involved. This is because the quality of a product is related to the quality of the material, the design of the product and the manufacturing process, and as tasks are subdivided, problems occurring in production cannot be solved completely by the sole effort of a single individual. Hence improvement of product quality involes man, machine, and material. This article explains how quality problems arising from surface mount technology are tackled by team effort in an organization via the implementation of a process-oriented total quality control system.     

EDM electrode manufacture using rapid tooling: a review

Electrical discharge machining (EDM) is a non-conventional process for the manufacture of complex or hard material parts that are difficult to machine by conventional machining processes. During EDM, the electrode shape is mirrored in the workpiece. As a result, problems are transferred on the electrode manufacturing process. Rapid tooling (RT) is a new technology which uses rapid prototyping (RP) models to reduce the time and cost of tool manufacture. The various methods of manufacturing RT electrodes, with respect to different materials and the incorporated supplementary processes, are classified in the present work. Recent international research work on RT electrodes is reviewed and the results on the performance of RT electrodes are tabulated.     

Individual latent error detection: is there a time and a place for the recall of past errors?

A task carried out in error creates a latent condition that can result in a future undesirable outcome if the error is not detected later. The paper presents a study of the relatively under-researched phenomenon of post-task latent error detection. Focusing on UK naval aircraft maintenance, it was hypothesised that time, location and systems cues influence individual latent error detection amongst naval air engineers who experience the phenomenon. The systems view of human error is combined with a multi-process approach to post-task latent error research, for which findings suggest that distributed cognition across the entire socio-technical system may be influential in post-task latent error detection. Directions for future research will be of benefit to those interested in furthering safety resilience using a systems approach to minimise the consequences arising from latent error.

Relevance to human factors/ergonomics theoryThe nature and extent of post-task latent error detection is explored using a systems approach, for which distributed cognition across the entire socio-technical system appears influential. The aim of current research is to develop interventions to further mitigate for latent errors and thus advance the systems application of ergonomics theory.     

混合工作日历下批量生产柔性作业车间多目标调度方法

提出了一种混合工作日历下批量生产柔性作业车间多目标调度方法。考虑设备的混合工作日历约束,构建了以生产周期最短、制造成本最低为优化目标的批量生产柔性作业车间多目标调度模型。设计了一种带精英策略的非支配排序遗传算法(NSGA II)求解该模型。算法中,采用“基于工序和设备的分段编码”方式分别对工序和设备进行编码;采用“基于工序和设备的分段交叉和变异方式”进行交叉和变异操作,采用“遗传算子改进策略”保证交叉、变异后子代个体的可行性;解码操作采用“基于平顺移动的原理”和“基于工作日历的时间推算技术”推算工序的调整开始、调整结束、加工开始和加工结束时刻。最后,通过案例分析验证了所提方法的有效性。