A Knowledge-Based System for Collecting and Integrating Production Information

Bruno, Giulia; Traini, Emiliano; Lombardi, Franco

doi:10.1007/978-3-030-28464-0_15

Cited by 6 publications

(3 citation statements)

References 15 publications

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“…Misalnya dapat diketahui produk apa saja yang sering dibeli dan jarang dibeli konsumen dalam setiap transaksi, dan diketahui saat terjadi peningkatan pembelian oleh konsumen dan juga melakukan pembangkangan di pasar dengan berbagai promosi, jika perilaku konsumen dalam pengambilan keputusan. pembuatannya dapat diketahui, maka perusahaan dapat merancang berbagai strategi pengendalian persediaan [12].…”

Section: Algoritma C45unclassified

Prinsip Klasifikasi Dan Data Mining Dengan Algoritma C4.5

Senubekti¹,

Dewi

2022

NUANSA

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Pertumbuhan yang cepat dan integrasi database memberikan ilmuwan, insinyur, dan pebisnis dengan sumber daya baru yang luas yang dapat dianalisis untuk membuat penemuan ilmiah, mengoptimalkan sistem industri, dan mengungkap pola yang berharga secara finansial. Untuk melakukan proyek analisis data besar ini, peneliti dan praktisi telah mengadopsi algoritme mapan dari statistik, pembelajaran mesin, jaringan saraf, dan basis data dan juga telah mengembangkan metode baru yang ditargetkan pada masalah data mining besar. Principles of Data Mining oleh David Hand, Heikki Mannila, dan Padhraic Smyth memberikan pengenalan kepada praktisi dan siswa tentang berbagai algoritma dan metodologi di area yang menarik ini. Pada penelitian ini digunakan algoritma C4.5. Sifat interdisipliner bidang ini cocok dengan ketiga penulis ini, yang keahliannya mencakup statistik, database, dan ilmu komputer. Hasilnya adalah sebuah buku yang tidak hanya memberikan detail teknis dan prinsip-prinsip matematika yang mendasari metode data mining, tetapi juga memberikan perspektif yang berharga tentang keseluruhan perusahaan.

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Section: Algoritma C45unclassified

Prinsip Klasifikasi Dan Data Mining Dengan Algoritma C4.5

Senubekti¹,

Dewi

2022

NUANSA

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“…The main issues associated with the OKP production are the frequent changes in the customer requirements and the inevitable changes occurring during the project management process that will cause delays in the final delivery [8]. For this reason, it is important to have a way of formally defining the work distribution among the different departments and allow them to communicate to manage the changes occurring during the project.…”

Section: Functionalities Of Core It Systemsmentioning

confidence: 99%

Integration of PLM, MES and ERP Systems to Optimize the Engineering, Production and Business

Avvaru

Bruno

Chiabert

et al. 2020

IFIP Advances in Information and Communication Technology

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In the era of Industry 4.0, the key factor for the success of a company is the cooperation among its different departments in order to share knowledge and information, thus optimizing time and cost. Three core IT systems are usually present in companies: Product Lifecycle Management (PLM), Manufacturing Execution system (MES) and Enterprise Resource Planning (ERP). PLM manages product and process design information, MES monitors and controls the execution of manufacturing process on the shop-floor, and ERP tracks business resources and the status of business commitments. This paper describes the integration process to optimize the engineering, production, business and management activities in a manufacturing company that operates according to the Oneof-a-Kind Production (OKP). It explains the architecture of such integration as well as the methodology applied for the customization of the PLM, MES and ERP systems available in the company. Moreover, the paper highlights the specific solutions developed to integrate the data management of the different systems as well as the IoT technology supporting the data communication.

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“…Previous works addressed the issue of structuring and formalising product-related knowledge [11][12][13][14][15], while several international research projects addressed the development of industrial knowledge sharing systems (e.g., amePLM [16], ICP4Life [17], Know4car [18], Manutelligence [19]). The benefits obtained by the symbiosis between design and manufacturing is highlighted in several papers [20,21].…”

Section: Related Workmentioning

confidence: 99%

Management and Production Engineering Review

Bruno

Faveto

Traini

2020

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Today, the changes in market requirements and the technological advancements are influencing the product development process. Customers demand a product of high quality and fast delivery at a low price, while simultaneously expecting that the product meet their individual needs and requirements. For companies characterized by a highly customized production, it is essential to reduce the trial-and-errors cycles to design new products and process. In such situation most of the company's knowledge relies on the lessons learnt by operators in years of work experience, and their ability to reuse this knowledge to face new problems. In order to develop unique product and complex processes in short time, it is mandatory to reuse the acquired information in the most efficient way. Several commercial software applications are already available for product lifecycle management (PLM) and manufacturing execution system (MES). However, these two applications are scarcely integrated, thus preventing an efficient and pervasive collection of data and the consequent creation of useful information. The aim of this paper is to develop a framework able to structure and relate information from design and execution of processes, especially the ones related to anomalies and critical situations occurring at the shop floor, in order to reduce the time for finalizing a new product. The framework has been developed by exploiting open source systems, such as ARAS PLM and PostgreSQL. A case study has been developed for a car prototyping company to illustrate the potentiality of the proposed solution.

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A Knowledge-Based System for Collecting and Integrating Production Information

Cited by 6 publications

References 15 publications

Prinsip Klasifikasi Dan Data Mining Dengan Algoritma C4.5

Prinsip Klasifikasi Dan Data Mining Dengan Algoritma C4.5

Integration of PLM, MES and ERP Systems to Optimize the Engineering, Production and Business

Management and Production Engineering Review

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