Evaluation of the changes in working limits in an automobile assembly line using simulation

The aim of the work presented in this paper consists of the development of a decision-making support system, based on discrete-event simulation models, of an automobile assembly line which was implemented within an Arena simulation environment and focused at a very specific class of production lines with a four closed-loop network configuration. This layout system reflects one of the most common configurations of automobile assembly and preassembly lines formed by conveyors. The sum of the number of pallets on the intermediate buffers, remains constant, except for the fourth closed-loop, which depends on the four-door car ratio (x) implemented between the door disassembly and assembly stations of the car body. Some governing equations of the four closed-loops are not compatible with the capacities of several intermediate buffers for certain values of variable x. This incompatibility shows how the assembly line cannot operate in practice for x0,97 in a stationary regime, due to the starvation phenomenon or the failure of supply to the machines on the production line. We have evaluated the impact of the pallet numbers circulating on the first closed-loop on the performance of the production line, translated into the number of cars produced/hour, in order to improve the availability of the entire manufacturing system for any value of x. Until the present date, these facts have not been presented in specialized literature. © 2012 American Institute of Physics

Simulation study for investment decisions on the EcoBoost camshaft machining line

Design/redesign of manufacturing systems is a complex, risky, and expensive task. Ford Motor Company’s Valencia Engine Plant faces this challenge as it plans to upgrade its machining and assembly lines to introduce the new EcoBoost engines. The research project described in this paper aimed to support the transition process particularly at the camshaft machining line by using simulation modelling techniques. A series of experiments was carried out using the simulation model developed, and recommendations were proposed based on the results of these experiments to support the decision as to where to invest on the line. The outcomes from the research project indicated that investment is required in terms of increasing the capacity of two bottleneck operations through retooling and improving the conveyor routing logic in one key area. Keywords: simulation modelling, closed-loop network, automotive production system

RANCANG BANGUN SISTEM PENGAMAN MENGGUNAKAN RFID

Penelitian ini bertujuan untuk merancang dan membuat sistem keamanan berbasis RFID (Radio Frequency Identification). Penelitian ini menggunakan metode R & D yaitu metode penelitian yang digunakan untuk menghasilkanproduk tertentu dan menguji keefektifan produk tersebut. Hasil penelitian menunjukan terdapat tiga tahap dalam membuat sistem keamanan berbasis RFID yaitu tahapan persiapan yang berkaitan dengan perancangan yang harus dipersiapkan demi menunjang proses pengerjaan, tahapan  pelaksanaan yaitu memulai proses perakitan sistem pengamanan otomatismenggunakan RFID serta tahap akhir menganalisa keberhasilan dari proses perakitan sistem pengaman otomatis

RANCANG BANGUN ALAT PENGUKUR JARAK AMAN MOBIL PADA AREA TEMPAT PARKIR UMUM MENGGUNAKAN SENSOR ULTRASONIC HC-SR04 DAN ARDUINO UNO

Penelitian ini bertujuan untuk mengetahui bagaimana tahapan membuat prototype alat pengukurjarak aman mobil menggunakan sensor ultrasonic HC-SR04 berbasis mikrokontroler arduino uno.Penelitian ini menggunakan metode R&D yaitu metode penelitian yang digunakan untuk menghasilkanproduk tertentu dan menguji keefektifan produk tersebut. Hasil penelitian menunjukan terdapat tiga tahapdalam membuat sistem pengukur jarak aman mobil yaitu tahapan persiapan yang berkaitan denganperancangan yang harus dipersiapkan demi menunjang proses pengerjaan, tahapan pelaksanaan yaitumemulai proses Alat Pengukur Jarak Aman Mobil Pada Area Tempat Parkir Umum Menggunakan SensorUltrasonic HC-SR04 Dan Arduino Uno serta tahap akhir menganalisa keberhasilan dari proses perakitansistem pengukur jarak aman mobil

Business analytics in industry 4.0: a systematic review

Recently, the term “Industry 4.0” has emerged to characterize several Information Technology and Communication (ICT) adoptions in production processes (e.g., Internet-of-Things, implementation of digital production support information technologies). Business Analytics is often used within the Industry 4.0, thus incorporating its data intelligence (e.g., statistical analysis, predictive modelling, optimization) expert system component. In this paper, we perform a Systematic Literature Review (SLR) on the usage of Business Analytics within the Industry 4.0 concept, covering a selection of 169 papers obtained from six major scientific publication sources from 2010 to March 2020. The selected papers were first classified in three major types, namely, Practical Application, Reviews and Framework Proposal. Then, we analysed with more detail the practical application studies which were further divided into three main categories of the Gartner analytical maturity model, Descriptive Analytics, Predictive Analytics and Prescriptive Analytics. In particular, we characterized the distinct analytics studies in terms of the industry application and data context used, impact (in terms of their Technology Readiness Level) and selected data modelling method. Our SLR analysis provides a mapping of how data-based Industry 4.0 expert systems are currently used, disclosing also research gaps and future research opportunities.The work of P. Cortez was supported by FCT - Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. We would like to thank to the three anonymous reviewers for their helpful suggestions

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Allocation of quality control stations in multistage manufacturing systems

The allocation of quality control stations (AQCS) in multistage manufacturing systems has been studied extensively over the decades. This paper reviews the existing approaches, models comparison and solution techniques applied in AQCS. The relevance of the models and the effectiveness of the inspection strategies are examined by developing a generalised model. The conducting simulation experiments show that as the number of workstation increases the processing tine to solve the problem increases significantly. This led to the development of a heuristic algorithm with local search. The performance the heuristic was compared with the optimization method based on complete enumeration method (CEM). It was found that the heuristic method can derive an acceptable solution significantly faster than the CEM. The review has shown that the most common techniques used are dynamic programming and non-linear programming. The paper suggests some biologically inspired optimisation algorithms can be of interest for further study. (C) 2011 Elsevier Ltd. All rights reserved