An automated coding and classification system with supporting database for effective design of manufacturing systems

The philosophy of group technology (GT) is an important concept in the design of flexible manufacturing systems and manufacturing cells. Group technology is a manufacturing philosophy that identifies similar parts and groups them into families. Beside assigning unique codes to these parts, group technology developers intend to take advantage of part similarities during design and manufacturing processes. GT is not the answer to all manufacturing problems, but it is a good management technique with which to standardize efforts and eliminate duplication. Group technology classifies parts by assigning them to different families based on their similarities in: (1) design attributes (physical shape and size), and/or (2) manufacturing attributes (processing sequence). The manufacturing industry today is process focused; departments and sub units are no longer independent but are interdependent. If the product development process is to be optimized, engineering and manufacturing cannot remain independent any more: they must be coordinated. Each sub-system is a critical component within an integrated manufacturing framework. The coding and classification system is the basis of CAPP and the functioning and reliability of CAPP depends on the robustness of the coding system. The proposed coding system is considered superior to the previously proposed coding systems, in that it has the capability to migrate into multiple manufacturing environments. This article presents the design of a coding and classification system and the supporting database for manufacturing processes based on both design and manufacturing attributes of parts. An interface with the spreadsheet will calculate the machine operation costs for various processes. This menu-driven interactive package is implemented using dBASE-IV. Part Family formation is achieved using a KAMCELL package developed in TURBO Pascal.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46606/1/10845_2004_Article_BF00123696.pd

Manufacturing decision support systems/ Hamid R. Parsaei; Sai Kolli; Thomas R Hanley (edt)

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A Methodology Of Forming Manufacturing Cells Using Manufacturing And Design Attributes

This study develops a methodology for forming machine cells using part\u27s design and manufacturing dissimilarities. The proposed methodology is divided into two sequential phases. In phase I parts are grouped into families based upon their design and manufacturing attributes. In phase II, the machines are grouped into manufacturing cells based on relevant operational costs and the various cells are assigned part families using an optimization technique. © 1992

A Survey Of Design Methods For Manufacturing Cells

In the recent years a new manufacturing system has emerged known as Cellular Manufacturing (CM) which utilizes the philosophy of group technology. Cellular manufacturing also known as group production can be described as a manufacturing process which produces families of parts within a single line or a group of machines operated manually or automatically. This paper discuses the available techniques used for cluster analysis and design of manufacturing cells and also illustrates a list of available methods and techniques used for clustering and their application in the manufacturing area. © 1993

Controlling Safety of Artificial Intelligence-Based Systems in Healthcare

Artificial intelligence (AI)-based systems have achieved significant success in healthcare since 2016, and AI models have accomplished medical tasks, at or above the performance levels of humans. Despite these achievements, various challenges exist in the application of AI in healthcare. One of the main challenges is safety, which is related to unsafe and incorrect actions and recommendations by AI algorithms. In response to the need to address the safety challenges, this research aimed to develop a safety controlling system (SCS) framework to reduce the risk of potential healthcare-related incidents. The framework was developed by adopting the multi-attribute value model approach (MAVT), which comprises four symmetrical parts: extracting attributes, generating weights for the attributes, developing a rating scale, and finalizing the system. The framework represents a set of attributes in different layers and can be used as a checklist in healthcare institutions with implemented AI models. Having these attributes in healthcare systems will lead to high scores in the SCS, which indicates safe application of AI models. The proposed framework provides a basis for implementing and monitoring safety legislation, identifying the risks in AI models’ activities, improving human-AI interactions, preventing incidents from occurring, and having an emergency plan for remaining risks

Effectiveness of Student Learning-a Comparison between Online & Face-To-Face Formats

Abstract The effectiveness of delivery systems for engineering courses has been long debated. In this study, two modes of delivery systems were compared, an online system, and a conventional face-to-face system to two cohorts of undergraduate students. To reduce variability, both courses were instructed by the same instructor, using the same textbook, and accompanied the same instructional material. The face-to-face class (control group) met twice a week for 90 minutes each session. The instructional material for the online students (experimental group) was made available to students via a secure website in an asynchronous mode. In addition, an audio version of the lecture materials was embedded using an internet-software for the online version of the course. The grade point averages (GPAs) of both groups of students were compared to ensure that both groups are comparable. A uniform pre-test was administered to both groups to identify any significant prior knowledge about the subject matter between these two groups. Several hypotheses were tested to assess the overall effectiveness of the online course in comparison to the traditional in-class lectures. In addition, other factors such as gender, and class standing were compared and analyzed