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Expert systems
Published in József Farkas, Károly Jármai, Analysis and Optimum Design of Metal Structures, 2020
The production system has been the most favourable representation approach for building computer ES-s. A production system is a collection of rules, which consist of an IF part and a THEN part or antecendent-consequent or situation-action parts. RULE NIF [ { antecendent 1 } …. { antecendent n } ]THEN [{consequent 1 with certainty c1 } …. { consequent n with certainty cn } ]
Computerized Process Control in Industrial Cooking Operations
Published in Gauri S. Mittal, Computerized Control Systems in the Food Industry, 2018
The keys to competitiveness are high product quality and product profile, good service, reliable deliveries, and lower cost [5]. This chapter presents different tools and aids involving computers that are used for industrial cooking operations in food production. Using the tools can increase output and efficiency in the production system. The chapter discusses trends, process descriptions, and developments in computerized process control in industrial cooking operations. Then it gives a more detailed look at both on-line and off-line computerized control systems. Finally, a few thoughts on the future in this field are given.
Hierarchical RNN-based framework for throughput prediction in automotive production systems
Published in International Journal of Production Research, 2023
Mengfei Chen, Richard Furness, Rajesh Gupta, Saumuy Puchala, Weihong (Grace) Guo
Recently, there is a growing body of literature on developing data-driven or artificial intelligence (AI)-based methods for production system analysis (Tao et al. 2018; Kuo and Kusiak 2019; Arinez et al. 2020). These approaches can overcome the limitations of traditional models, by taking advantage of the rich production data in modern production systems. Studies show that the system throughput is highly correlated to machine status data (e.g. the time that a machine is working or idle). For example, Popova and Wilson (2000) developed an adaptive time dynamic model based on Bayesian models to predict the production volume for a lathe machine based on its operational data. At the system level, many AI-based approaches have been developed to analyse the throughput bottleneck machine(s) (see review by Subramaniyan et al. 2021). However, as will be discussed in Section 2.1, the existing methods have some limitations that make them not directly applicable to general throughput prediction problems.
Analysis of a two-critical-number production policy in an M/G-type production system with waiting time information
Published in International Journal of Management Science and Engineering Management, 2020
For each queue of type }, let denote the total-expected time when the queue is in state during its busy period, where . When a queue of type is in state , the corresponding state during the period of type in the production system is , namely, for each state in the original production system, the corresponding state for the queue of type is where
(Smart CPS) Integrated application in intelligent production and logistics management: technical architectures concepts and business model analyses for the customised facial masks manufacturing
Published in International Journal of Computer Integrated Manufacturing, 2019
Chang Liu, Yunzhu Zhou, Yutong Cen, Dongtao Lin
Industry 4.0 outdoes its predecessors in mass customisation, higher quality, increasing productivity, and a shorter time between production and marketisation, according to Zhong, Klotz, and Newman (2017). Therefore, by building CPS based on industrial automation and using the application program of network physical production system, the approach proposed in this study combines the intelligent production module of artificial intelligence and big data analytics to provide a computer integrated production system based on Industry 4.0 for the facial mask industry. Physical stores are included to collect chemical samples from consumers’ faces. With the intelligent logistics management module based on big data, these chemical samples will be sent to the factory for further detailed analysis, where the best formula for the facial mask would be developed, followed by the integrated manufacturing process. Production managers use mobile monitoring terminals such as laptop computers and smartphones to perform real-time monitoring over the entire process and make dynamical adjustments if necessary. In particular, the logistics distribution, which is big-data-analytics-based, router-supported, and supported by MapReduce mode technology with Hadoop framework and ZigBee wireless sensor network technology, secures a stable and efficient logistics process. According to Karaköse and Hasan (2017), big data analytics increases customers’ satisfaction because it reduces their waiting time.