scholarly journals Smart Monitoring of Manufacturing Systems for Automated Decision-Making: A Multi-Method Framework

Sensors ◽  
2021 ◽  
Vol 21 (20) ◽  
pp. 6860
Author(s):  
Chen-Yang Cheng ◽  
Pourya Pourhejazy ◽  
Chia-Yu Hung ◽  
Chumpol Yuangyai
Keyword(s):  
Decision Making ◽  
Data Collection ◽  
Manufacturing Systems ◽  
Real Data ◽  
Computationally Efficient ◽  
Time Data ◽  
Intelligent Decision Making ◽  
Noninvasive Sensors ◽  
And Performance ◽  
Manufacturing Environments

Smart monitoring plays a principal role in the intelligent automation of manufacturing systems. Advanced data collection technologies, like sensors, have been widely used to facilitate real-time data collection. Computationally efficient analysis of the operating systems, however, remains relatively underdeveloped and requires more attention. Inspired by the capabilities of signal analysis and information visualization, this study proposes a multi-method framework for the smart monitoring of manufacturing systems and intelligent decision-making. The proposed framework uses the machine signals collected by noninvasive sensors for processing. For this purpose, the signals are filtered and classified to facilitate the realization of the operational status and performance measures to advise the appropriate course of managerial actions considering the detected anomalies. Numerical experiments based on real data are used to show the practicability of the developed monitoring framework. Results are supportive of the accuracy of the method. Applications of the developed approach are worthwhile research topics to research in other manufacturing environments.

scholarly journals Optimal Prescriptive Trees

2019 ◽  
Vol 1 (2) ◽  
pp. 164-183 ◽  
Author(s):  
Dimitris Bertsimas ◽  
Jack Dunn ◽  
Nishanth Mundru
Keyword(s):  
Decision Making ◽  
Linear Models ◽  
State Of The Art ◽  
Online Advertising ◽  
Real Data ◽  
Attractive Alternative ◽  
High Quality ◽  
And Performance ◽  
Multiple Treatments ◽  
And Personalized Medicine

Motivated by personalized decision making, given observational data [Formula: see text] involving features [Formula: see text], assigned treatments or prescriptions [Formula: see text], and outcomes [Formula: see text], we propose a tree-based algorithm called optimal prescriptive tree (OPT) that uses either constant or linear models in the leaves of the tree to predict the counterfactuals and assign optimal treatments to new samples. We propose an objective function that balances optimality and accuracy. OPTs are interpretable and highly scalable, accommodate multiple treatments, and provide high-quality prescriptions. We report results involving synthetic and real data that show that OPTs either outperform or are comparable with several state-of-the-art methods. Given their combination of interpretability, scalability, generalizability, and performance, OPTs are an attractive alternative for personalized decision making in a variety of areas, such as online advertising and personalized medicine.

scholarly journals Cooperative Product Agents to Improve Manufacturing System Flexibility: A Model-Based Decision Framework

2021 ◽  
Author(s):  
Ilya Kovalenko ◽  
Efe Balta ◽  
Dawn Tilbury ◽  
Kira Barton
Keyword(s):  
Decision Making ◽  
Control Strategy ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Timed Automata ◽  
Shop Floor ◽  
Intelligent Software ◽  
Multi Agent ◽  
Agent Control ◽  
And Performance

Due to the advancements in manufacturing system technology and the ever-increasing demand for personalized products, there is a growing desire to improve the flexibility of manufacturing systems. Multi-agent control is one strategy that has been proposed to address this challenge. The multi-agent control strategy relies on the decision making and cooperation of a number of intelligent software agents to control and coordinate various components on the shop floor. One of the most important agents for this control strategy is the product agent, which is the decision maker for a single part in the manufacturing system. To improve the flexibility and adaptability of the product agent and its control strategy, this work proposes a direct and active cooperation framework for the product agent. The directly and actively cooperating product agent can identify and actively negotiate scheduling constraints with other agents in the system. A new modeling formalism, based on priced timed automata, and an optimization-based decision making strategy are proposed as part of the framework. Two simulation case studies showcase how direct and active cooperation can be used to improve the flexibility and performance of manufacturing systems.

scholarly journals Cooperative Product Agents to Improve Manufacturing System Flexibility: A Model-Based Decision Framework

2021 ◽  
Author(s):  
Ilya Kovalenko ◽  
Efe Balta ◽  
Dawn Tilbury ◽  
Kira Barton
Keyword(s):  
Decision Making ◽  
Control Strategy ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Timed Automata ◽  
Shop Floor ◽  
Intelligent Software ◽  
Multi Agent ◽  
Agent Control ◽  
And Performance

Due to the advancements in manufacturing system technology and the ever-increasing demand for personalized products, there is a growing desire to improve the flexibility of manufacturing systems. Multi-agent control is one strategy that has been proposed to address this challenge. The multi-agent control strategy relies on the decision making and cooperation of a number of intelligent software agents to control and coordinate various components on the shop floor. One of the most important agents for this control strategy is the product agent, which is the decision maker for a single part in the manufacturing system. To improve the flexibility and adaptability of the product agent and its control strategy, this work proposes a direct and active cooperation framework for the product agent. The directly and actively cooperating product agent can identify and actively negotiate scheduling constraints with other agents in the system. A new modeling formalism, based on priced timed automata, and an optimization-based decision making strategy are proposed as part of the framework. Two simulation case studies showcase how direct and active cooperation can be used to improve the flexibility and performance of manufacturing systems.

Determining Network Control Solution Designs for Manufacturing Systems

2008 ◽  
Author(s):  
James Moyne ◽  
Dawn Tilbury
Keyword(s):  
Decision Making ◽  
Manufacturing Systems ◽  
Network Control ◽  
Optimal Solutions ◽  
Control Solution ◽  
Design Decisions ◽  
Network Operation ◽  
Effective Decision ◽  
Effective Decision Making ◽  
And Performance

In addressing the need for manufacturing systems that are more reconfigurable and flexible, there is an ever-increasing focus on utilizing networks at all levels to support control, diagnostics and safety functionality. Issues of performance and cost must be addressed. Further, making an appropriate network choice often involves examining the application environment rather than just universally applying a set of heuristics. The result is that network decisions, such as protocol, medium, and partitioning, are often made with incomplete or inappropriately prioritized information, leading to sub-optimal solutions in terms of both cost and performance. Three perspectives of information are needed for effective decision-making in network control system (NCS) deployment, namely theoretical, experimental and analytical. Theoretical involves understanding network operation, identifying metrics for NCS performance in the application environment, and mathematically evaluating the solution candidates with respect to these metrics. Experimental requires collecting and evaluating experimental data on particular aspects of network operation that are important to the application environment. Analytical involves a weighted cost analysis of the tradeoffs involved in network decision making and incorporates the results of theoretical and experimental analysis. In combining these three information perspectives, a methodology for making NCS design decisions is provided that allows the user to appropriately incorporate the application environment. An application of this methodology to a reconfigurable factory testbed demonstrates its use and effectiveness.

Data-centric Maintenance and Operational Knowledge and Its Impact on Classification

2015 ◽  
Author(s):  
Domenic P. Carlucci ◽  
Robert Conachey ◽  
John B. Hagan
Keyword(s):  
Decision Making ◽  
Data Collection ◽  
Asset Management ◽  
Performance Data ◽  
Monitoring Systems ◽  
Maintenance Planning ◽  
Effective Management ◽  
Management Planning ◽  
Maintenance Activities ◽  
And Performance

The monitoring of machinery condition, performance, and maintenance activities continues to be vital to the effective management of marine assets. Identifying key data, developing a data collection protocol, and analyzing the data are key to effective management. Planning for these activities should rely on risk and reliability techniques. Integrating data collection with the vessel’s or asset’s control and monitoring systems can reduce crew burden and simplify an often complex puzzle of qualifying and analyzing condition and performance data into a standardized process for maintenance planning and decision making related to asset operations. The information gathered from these processes can create a knowledge loop that, when implemented in an enterprise asset management (EAM) strategy, can improve current operational execution and influence the next generation of marine asset designs. Classification societies can apply this information for effective surveys and Rules improvement.

scholarly journals Data-Driven Decision-Making

2021 ◽  
pp. 47-59
Author(s):  
Sophie J. Barbu ◽  
Karen McDonald ◽  
Lisceth Brazil-Cruz ◽  
Lisa Sullivan ◽  
Linda F. Bisson
Keyword(s):  
Decision Making ◽  
Data Collection ◽  
Data Driven ◽  
Time Data ◽  
Institutional Level ◽  
Data Analyses ◽  
Level Data ◽  
Effective Decision ◽  
Effective Decision Making ◽  
Equity And Inclusion

AbstractAddressing barriers to inclusion requires understanding the nature of the problem at the institutional level. Data collection and assessment are both crucial for this aim. In this chapter, we describe two important classes of data: (1) data on diversity that define the potential nature of the issues at stake and the need for change, and (2) data on assessing the usefulness of new programs, processes, and policies in creating a more diverse institution. Both sets of data are important for effective decision-making. At the same time, data analyses can be challenging because issues of equity and inclusion are complex and determining the basis of comparison or the “ideal” diversity target can be difficult. Nevertheless, data gathering and analysis are critical to assess progress and to provide a basis for both accountability and efficacy. Moreover, the ability to document that a problem indeed exists will help justify the need for change and, ideally, spur corrective action.

scholarly journals Validation of performance assessment instrument on futsal game in extracurricular activities

2019 ◽  
Vol 5 (2) ◽  
pp. 175
Author(s):  
Mahir Dwi Nugroho ◽  
Tomoliyus Tomoliyus
Keyword(s):  
Decision Making ◽  
Data Collection ◽  
Performance Assessment ◽  
Extracurricular Activities ◽  
Content Validity ◽  
Delphi Technique ◽  
Research Evaluation ◽  
Assessment Instrument ◽  
The Subject ◽  
And Performance

The research is aimed at evaluating the content validity and performance of an assessment instrument, based on futsal games in extracurricular activities. This is very important because of its ability to review objectively and also the application as a material for coach evaluation. In addition, the method used was research evaluation, with documents as the subject, and Delphi technique was applied in data collection by 5 experts. Furthermore analysis involved the use of formula Content Validity Ratio (CVR), which was developed by Lawshe, and the results showed the values obtained to be above 0.05, with indicators of Decision Making being 1.00, Skill = 1.00, Support = 0. 60 and Re-position = 1.00. In conclusion, the performance assessment instrument based on futsal game in extracurricular activities was observed to have high value validity contents.

Characterization and Utilization of the Intelligent Decision Making Methodology to Improve Quality and Precision in the Machining Process

2016 ◽  
Vol 686 ◽  
pp. 92-99 ◽  
Author(s):  
Gökcen Bas ◽  
Numan M. Durakbasa ◽  
Jorge Bauer ◽  
Gunther Poszvek
Keyword(s):  
Decision Making ◽  
Numerical Analysis ◽  
Quality Management ◽  
Manufacturing Systems ◽  
Manufacturing Industry ◽  
Machining Process ◽  
Management Approach ◽  
Improve Quality ◽  
Intelligent Decision Making ◽  
Intelligent Decision

Today’s manufacturing industry, as the backbone of European manufacturing, faces challenges in improved quality and precision requirements to operate competitively. Due to the complexity of the manufacturing systems, enhancement of the competitiveness can be achieved by systematic modeling, characterization and efficient exploitation of knowledge in the processes integrated with the quality methodology under guidance of the international standards.This paper provides an intelligent decision making methodology enabled by numerical analysis for developing a mechanism in the manufacturing industry firstly by modeling the processes integrated with the quality management approach as well as applying high precision metrology techniques in a laboratory.

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