Automatic Color Inspection for Colored Wires in Electric Cables

In this paper, an automatic optical inspection system for checking the sequence of colored wires in electric cable is presented. The system is able to inspect cables with flat connectors differing in the type and number of wires. This variability is managed in an automatic way by means of a self-learning subsystem and does not require manual input from the operator or loading new data to the machine. The system is coupled to a connector crimping machine and once the model of a correct cable is learned, it can automatically inspect each cable assembled by the machine. The main contributions of this paper are: (i) the self-learning system; (ii) a robust segmentation algorithm for extracting wires from images even if they are strongly bent and partially overlapped; (iii) a color recognition algorithm able to cope with highlights and different finishing of the wire insulation. We report the system evaluation over a period of several months during the actual production of large batches of different cables; tests demonstrated a high level of accuracy and the absence of false negatives, which is a key point in order to guarantee defect-free productions

In-process monitoring in electrical machine manufacturing: A review of state of the art and future directions

Manual operations feature prominently in the manufacture of many electrical machines. Even though high-volume electrical machine manufacture is dominated by automation, several manufacturing operations continue to involve manual intervention because of the complexity of such operations makes them heavily reliant on high dexterity manual skills and experience. However, quality can be variable due to human involvement. Currently, in order to maintain a high precision of control and required tolerances of the final machine, inspection is performed at various steps during manufacturing and assembly. Detecting a defect at these end-of-line tests can result in significant wasted time and costs due to rework or scrappage. The solution to this problem lies in in-process monitoring particularly for error prone manual operations. This paper presents a literature review of the state-of-the-art available techniques and limitations in process monitoring within the context of electrical machine manufacturing. To quantify the degree of manual activities in process monitoring within electrical machine manufacture, a structured survey of UK based companies was conducted, identifying specific error prone manual processes to target, and gaps in inspection. The survey identified that a significant proportion of activities in electrical machine manufacture are manual, or semi-automated with manual interventions. However, literature review revealed only a limited research in in-process monitoring of manual operations in this area. Finally, two case studies are presented where case study 1 presents a framework for digitisation of a variety of manual manufacturing tasks, and case study 2 demonstrates real-time capture, modelling and analysis of deformable linear objects in electrical machine manufacturing

A lean transformation in low volume space manufacturing

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, Thesis (S.M. in Ocean Systems Management)--Massachusetts Institute of Technology,Dept. of Ocean Engineering; in conjunction with the Leaders for Manufacturing Program at MIT, 2003.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections."June 2003."Includes bibliographical references (leaves 59-60).by Lincoln J. Sise.S.M.in Ocean Systems ManagementM.B.A

Packaging Technologies for Millimeter Scale Microsystems in Harsh Environment Applications

Microsystems capable of sensing temperature, pressure and other parameters are needed for many applications, for example, gathering information in downhole environments for oil and gas exploration. Certain target locations limit the size of the microsystems to millimeter or even sub-millimeter scale. In addition, the high temperature, high pressure, and corrosive ambient environments are challenging for microsystems. Target environments include 125°C temperature, 50 MPa pressure, and salinity standards consistent with American Petroleum Institute (API) brine (8% NaCl + 2% CaCl2). Other chemicals including hydrocarbons and cement slurry are also found in these environments. The system package plays a critical role as it protects the system components against environment, while also providing the physical coupling to the environment, e.g., for communication modules and pressure sensors. The package must be made of mechanically and chemically robust materials. High temperature assembly steps must be avoided in the packaging process (such as bonding above 200°C), because these steps are generally incompatible with embedded batteries and polymer-based sensors. The development of system package and relevant technologies is the focus of this dissertation. This dissertation first describes the design and fabrication of sapphire-on-steel packages in two sizes (0.8 mm and 8 mm), which are capable of isolating high pressure while allowing optical communication. These packages have been operated with embedded electronics at 125ºC and ≈70 MPa in API brine, hydrocarbons, and cement slurry. Additionally, polymer-in-tube packages are reported, which allow the embedded pressure sensors to couple with the environment. These packages have been successfully operated with embedded electronics and sensors at 125ºC and 50 MPa in API brine. A third approach of encapsulation that is reported involves polymer film encapsulation, which has the potential to significantly improve the chemical resistance of microsystems. Finally a batch-mode packaging process is presented based on micro-crimping, enabling room temperature assembly for sub-millimeter scale packages made by metal alloys. This packaging process has been demonstrated by a 5×5 array of 0.5 mm packages. These packages have survived at least 200 MPa pressure and at least 72 h in API brine.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/135761/1/yushuma_1.pd

Hangprinter for large scale additive manufacturing using fused particle fabrication with recycled plastic and continuous feeding

The life cycle of plastic is a key source of carbon emissions. Yet, global plastics production has quadrupled in 40 years and only 9 % has been recycled. If these trends continue, carbon emissions from plastic wastes would reach 15 % of global carbon budgets by 2050. An approach to reducing plastic waste is to use distributed recycling for additive manufacturing (DRAM) where virgin plastic products are replaced by locally manufactured recycled plastic products that have no transportation-related carbon emissions. Unfortunately, the design of most 3-D printers forces an increase in the machine cost to expand for recycling plastic at scale. Recently, a fused granular fabrication (FGF)/fused particle fabrication (FPF) large-scale printer was demonstrated with a GigabotX extruder based on the open source cable driven Hangprinter concept. To further improve that system, here a lower-cost recyclebot direct waste plastic extruder is demonstrated and the full designs, assembly and operation are detailed. The <$1,700 machine’s accuracy and printing performance are quantified, and the printed parts mechanical strength is within the range of other systems. Along with support from the Hangprinter and DUET3 communities, open hardware developers have a rich ecosystem to modify in order to print directly from waste plastic for DRAM

Understanding and improving the manufacturing and changeover process in Saudi Arabian business - a multiple case study approach

The importance of the changeover process in the manufacturing industry is becoming widely recognised. Changeover is a complete process of changing between the manufacture of one product to manufacture of an alternative product until specified production and quality rates are reached. The initiatives to improve changeover exist in industry, as better changeover process typically contribute to improved quality performance. A high-quality and reliable changeover process can be achieved through implementation of continuous or radical improvements. This research examines the changeover process of Saudi Arabian manufacturing firms because Saudi Arabia’s government is focused on the expansion of GDP and increasing the number of export manufacturing firms. Furthermore, it is encouraging foreign manufacturing firms to invest within Saudi Arabia. These initiatives, therefore, require that Saudi manufacturing businesses develop the changeover practice in order to compete in the market and achieve the government’s objectives. Therefore, the aim of this research is to discover the current status of changeover process implementation in Saudi Arabian manufacturing businesses. To achieve this aim, the main objective of this research is to develop a conceptual model to understand and examine the effectiveness of the changeover process within Saudi Arabian manufacturing firms, facilitating identification of those activities that affect the reliability and high-quality of the process. In order to provide a comprehensive understanding of this area, this research first explores the concept of quality management and its relationship to firm performance and the performance of manufacturing changeover. An extensive body of literature was reviewed on the subject of lean manufacturing and changeover practice. A research conceptual model was identified based on this review, and focus was on providing high-quality and reliable manufacturing changeover processes during set-up in a dynamic environment. Exploratory research was conducted in sample Saudi manufacturing firms to understand the features of the changeover process within the manufacturing sector, and as a basis for modifying the proposed conceptual model. Qualitative research was employed in the study with semi-structured interviews, direct observations and documentation in order to understand the real situation such as actual daily practice and current status of changeover process in the field. The research instrument, the Changeover Effectiveness Assessment Tool (CEAT) was developed to evaluate changeover practices. A pilot study was conducted by examining the CEAT, proposed for the main research. Consequently, the conceptual model was modified and CEAT was improved in response to the pilot study findings. Case studies have been conducted within eight Saudi manufacturing businesses. These case studies assessed the implementation of manufacturing changeover practice in the lighting and medical products sectors. These two sectors were selected based on their operation strategy which was batch production as well as the fact that they fulfilled the research sampling strategy. The outcomes of the research improved the conceptual model, ultimately to facilitate the firms’ adoption and rapid implementation of a high-quality and reliability changeover during the set-up process. The main finding of this research is that Quality’s factors were considering the lowest levels comparing to the other factors which are People, Process and Infrastructure. This research contributes to enable Saudi businesses to implement the changeover process by adopting the conceptual model. In addition, the guidelines for facilitating implementation were provided in this thesis. Therefore, this research provides insight to enable the Saudi manufacturing industry to be more responsive to rapidly changing customer demands

Augmented classification for electrical coil winding defects

A green revolution has accelerated over the recent decades with a look to replace existing transportation power solutions through the adoption of greener electrical alternatives. In parallel the digitisation of manufacturing has enabled progress in the tracking and traceability of processes and improvements in fault detection and classification. This paper explores electrical machine manufacture and the challenges faced in identifying failures modes during this life cycle through the demonstration of state-of-the-art machine vision methods for the classification of electrical coil winding defects. We demonstrate how recent generative adversarial networks can be used to augment training of these models to further improve their accuracy for this challenging task. Our approach utilises pre-processing and dimensionality reduction to boost performance of the model from a standard convolutional neural network (CNN) leading to a significant increase in accuracy

Southwest Research Institute assistance to NASA in biomedical areas of the technology utilization program Final report, 1 Feb. 1969 - 24 Aug. 1970

Research progress in technology transfer by NASA Biomedical Application Tea

Automation and robotics for the National Space Program

The emphasis on automation and robotics in the augmentation of the human centered systems as it concerns the space station is discussed. How automation and robotics can amplify the capabilities of humans is detailed. A detailed developmental program for the space station is outlined