Application of Lean Analyses and Computer Simulation in Complex Product Manufacturing Process

Author(s):  
Dorota Stadnicka ◽  
Maksymilian Mądziel
2017 ◽  
Vol 13 (06) ◽  
pp. 22
Author(s):  
Qu Jing Lei ◽  
Li Shao Bo ◽  
Chen Jing Kun

Complex Event Processing (CEP), which can identify patterns of interest from a large number of continuous data steam, is becoming more and more popular in manufacturing process monitoring. CEP rules are specified manually by domain expert, which is a limiting factor for its application in manufacturing enterprises. How to analysis historical data and automatically generate CEP rules is becoming a challenge research. This paper proposed a model of autoCEP for online monitoring in product manufacturing, which can automatically generate CEP rules based on association rules mining in key processes. First, the key quality factors in manufacturing process were extracted by grey entropy correlation analysis. Then, association rules mining method based on product process constraints was used to find the association rules between key factors and product quality. At last, the extracted rules are algorithmically transformed into CEP rules. The experimental results show the effectiveness and practicability of the proposed method.


Author(s):  
Richard Mathieu

Every finished product has gone through a series of transformations. The process begins when manufacturers purchase the raw materials that will be transformed into the components of the product. The parts are then supplied to a manufacturer, who assembles them into the finished product and ships the completed item to the consumer. The transformation process includes numerous activities (Levary, 2000). Among them are • Designing the product • Designing the manufacturing process • Determining which component parts should be produced in house and which should be purchased from suppliers • Forecasting customer demand • Contracting with external suppliers for raw materials or component parts • Purchasing raw materials or component parts from suppliers • Establishing distribution channels for raw materials and component parts from suppliers to manufacturer • Establishing of distribution channels to the suppliers of raw materials and component parts • Establishing distribution channels from the manufacturer to the wholesalers and from wholesalers to the final customers • Manufacturing the component parts • Transporting the component parts to the manufacturer of the final product • Manufacturing and assembling the final product • Transporting the final product to the wholesalers, retailers, and final customer Each individual activity generates various data items that must be stored, analyzed, protected, and transmitted to various units along a supply chain. A supply chain can be defined as a series of activities that are involved in the transformation of raw materials into a final product, which a customer then purchases (Levary, 2000). The flow of materials, component parts, and products is moving downstream (i.e., from the initial supply sources to the end customers). The flow of information regarding the demand for the product and orders to suppliers is moving upstream, while the flow of information regarding product availability, shipment schedules, and invoices is moving downstream. For each organization in the supply chain, its customer is the subsequent organization in the supply chain, and its subcontractor is the prior organization in the chain.


Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5677
Author(s):  
Anqi Zhang ◽  
Yihai He ◽  
Xiao Han ◽  
Yao Li ◽  
Xiuzhen Yang ◽  
...  

For intelligent manufacturing systems, there are many deviations in operational characteristics, and the coupling effect of harmful operational characteristics leads to the variations in quality of the work-in-process (WIP) and the degradation of the reliability of the finished product, which is reflected as a loss of product manufacturing reliability. However, few studies on the modeling of product manufacturing reliability and mechanism analysis consider the operating mechanism and the coupling of characteristics. Thus, a novel modeling approach based on quality variations centered on the coupling of operational characteristics is proposed to analyze the formation mechanism of product manufacturing reliability. First, the PQR chain containing the co-effects among the manufacturing system performance (P), the manufacturing process quality (Q), and the product manufacturing reliability (R) is elaborated. The connotation of product manufacturing reliability is defined, multilayered operational characteristics are determined, and operational data are collected by smart sensors. Second, on the basis of the coupling effect in the PQR chain, a multilayered product quality variation model is proposed by mining operational characteristic data obtained from sensors. Third, an integrated product manufacturing reliability model is presented on the basis of the variation propagation mechanism of the multilayered product quality variation model. Finally, a camshaft manufacturing reliability analysis is conducted to verify the validity of the proposed method. The method proposed in this paper proved to be effective for evaluating and predicting the product reliability in the smart manufacturing process.


2010 ◽  
Vol 139-141 ◽  
pp. 1455-1459 ◽  
Author(s):  
Qi Cheng Zhang ◽  
Lin Zhang ◽  
Yong Liang Luo ◽  
Bao Lu Wang

Experience accumulation and reuse are very important for manufacturing of complex product. However, there is no mechanism to support such function in the integrated manufacturing system based on semantic SOA which is generally accepted as an effective approach to raise productivity. Specific to this problem, we propose a solution by building a case-base in semantic SOA to improve the traditional framework, in which case-base can accumulates the experiences by case study and reuse them by case retrieve. In this paper, the new architecture and workflow of the semantic SOA with build-in case-base is designed, merging and maximizing the advantages of both case-base and SOA to make up the lack of experience accumulation and reuse mechanism. Then, combined with field characteristics of complex products’ manufacturing process, construction and implementation concerning key technologies and methods of case-base are comprehensively elaborated.


2014 ◽  
Vol 607 ◽  
pp. 89-94
Author(s):  
Ai Ming Xu ◽  
Jian Min Gao ◽  
Kun Chen ◽  
Fu Min Chen ◽  
Zhao Wang

Workshop is gathered place and exchange centre of product manufacturing process information (PMPI), which is divided by enterprise heterogeneous systems. This led to the integration and sharing difficulty of PMPI and constrains the information system application in workshop, like MES. To solve this problem an information integration method based on semantic BOM was proposed. Firstly, a global ontology model USBOM of PMPI was constructed which given the unified semantic description of PMPI. Based on USBOM a PMPI integration framework was proposed. Finally, a workshop product manufacturing monitoring system was used as an example to verify the feasibility of this approach.


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