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Both the need for the introduction of automated optical inspection (AOI) systems in the PCB manufacturing process and the requirements, technically and on economic grounds, placed on such equipment are discussed in detail. Furthermore, emphasis is placed on the description of commonly used AOI concepts. The paper ends with a check list containing the most important questions concerning any system's capabilities.

Examines the use of laser‐induced fluorescence for the inspection of printed circuit boards. Discusses how it works, how it compares with other inspection options and what advantages it offers, particularly for the inspection of low‐contrast materials. Concludes that laser‐based automated optical inspection (AOI) has major potential advantages compared with white‐light AOI equipment.

To present an overview of the research and development carried out by an EC Framework 6 part funded consortium, known as MICROSCAN, for the implementation of an in‐line PCB inspection prototype system that is capable of offering comprehensive defect detection.

Four non‐destructive testing inspection modules based on digital radiography (X‐ray) inspection, thermal inspection, automated‐optical inspection and acoustic inspection have been integrated to form a combined inspection system.

A proof in principle in‐line PCB inspection system, utilising four different inspection techniques, has been developed and demonstrated. The system is based on a generic mechanical, electrical and software communications platform culminating in a flexible system that enables the inspection modules to be used separately, together or interchanged to give the best results in terms of inspection coverage and inspection throughput.

In its current embodiment, the prototype is suited to inspection of high‐return PCBs, particularly those used in medical and aerospace products, rather than high‐throughput PCB production work. The X‐ray inspection module is the slowest inspection technique and combining four different inspection techniques reduces the inspection throughput of the whole system to that of the X‐ray inspection module. Further, trials and investigations need to be carried out to improve inspection throughput.

The novelty of the system is that it is the first time that four inspection techniques have been combined to give the capability of 100 per cent defect coverage.

This paper aims to study the component pick-and-place (P&P) defect patterns for different root causes based on automated optical inspection data and develop a root cause identification model using machine learning.

This study conducts experiments to simulate the P&P machine errors including nozzle size and nozzle pick-up position. The component placement qualities with different errors are inspected. This study uses various machine learning methods to develop a root cause identification model based on the inspection result.

The experimental results revealed that the wrong nozzle size could increase the mean and the standard deviation of component placement offset and the probability of component drop during the transfer process. Moreover, nozzle pick-up position can affect the rotated component placement offset. These root causes of defects can be traced back using machine learning methods.

This study provides operators in surface mount technology assembly lines to understand the P&P machine error symptoms. The developed model can trace back the root causes of defects automatically in real line production.

The findings are expected to lead the regular preventive maintenance to data-driven predictive and reactive maintenance.

This paper aims to present the development of an automated inspection system (AIS) using an image-based analysis mechanism, called i-AIS. The development process of i-AIS used the Design Six Sigma (DSS) methodology. The steps of define, measure, analyze, design and verify (DMADV) are applied and integrated with specific analyses techniques of the quality function deployment (QFD), design failure mode effect analysis (DFMEA) and theory of inventive problem solving (TRIZ). The production process of adhesive tape is the focused case study in this research project, motivated by the high product defect rate complained by customers.

The development process of i-AIS was divided into five standard steps based on the DSS methodologies of DMADV. One of the key processes in this development was to systematically identify the right and intended features of i-AIS. This was carried out based on the application of the QFD technique. Another important process was to further investigate the possible causes of i-AIS failure, to function as intended. This investigative process was carried out based on the DFMEA technique, while the solution to minimize the risk of the identified failures was obtained from the TRIZ method. The final prototype of i-AIS was then presented in the design step.

Verification of the i-AIS prototype revealed its operation at an optimally intended mode that fulfilled the requirements of internal customers. Verification results also revealed that the sigma level has improved from 3.87 to 4.33. Meanwhile, the defect reduction rate is improved to 74.4% and downtime rate also recorded a significant improvement at 80.7% of reduction.

The presented research work is carried out based on a customized case study. Although the proposed methodology can be applied to others cases towards design-based solution, some modifications maybe required based on to the unique features of the case study under consideration.

The presented research project indicated that the proposed methodology was successful to facilitate a structured and systematic process towards defect identification, classification, evaluation and generation of a solution.

The paper presents the development process of an AIS by considering comprehensive managerial aspects that are currently absent in the literature. An integrated DSS structure is proposed to systematically guide the development of i-AIS. The related managerial aspects such as identification of critical defects problem, customer requirement mapping, prototype design analysis and comparison measurements before and after i-AIS installation are considered in this research project.

Electronic packaging technologies, such as pin grid arrays, increasingly small pitch surface mount, and double‐sided assemblies are all aimed towards the highest possible product density, with improved performance. The gap between inspection effectiveness and advances made in packaging technologies is becoming larger. As efforts proceed, to learn more about critical factors influencing reliability of solder joints, it is prudent to ensure that printed wiring assembly (PWA) design rules evolve to permit the broadest range of anticipated automated inspection requirements. The range of automated inspection technologies can all be made more effective through careful design of electronics for inspection. Significant opportunities lie in both PWA layout and design, as well as electronic component design, tolerancing, and standardisation. Many inspection issues are shared, but with increased recognition of digital radiography's unique capabilities; this discussion will emphasise X‐ray inspection issues.