An autonomous manufacturing system for adapting to disturbances

Park, Hong Seok; Tran, Ngoc-Hien

doi:10.1007/s00170-011-3229-2

Cited by 19 publications

(8 citation statements)

References 7 publications

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“…Meantime, parts should be smart and they need to know how they are manufactured and their current progress (Ding et al 2017b). Through autonomous interactions among parts and resources, production decisions, resource orchestration and execution control can be made by them collaboratively (Park and Tran 2011). The autonomy of smart parts and resources enhances the flexibility and response speed of smart shop floors.…”

Section: Cps/cpps and Autonomous Manufacturingmentioning

confidence: 99%

Defining a Digital Twin-based Cyber-Physical Production System for autonomous manufacturing in smart shop floors

Ding

Chan

Zhang

et al. 2019

International Journal of Production Research

328

106

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Smart manufacturing is the core idea of the fourth industrial evolution. For a smart manufacturing shop floor, real-time monitoring, simulation and prediction of manufacturing operations are vital to improve the production efficiency and flexibility. In this paper, the Cyber-Physical System (CPS) and Digital Twin technologies are introduced to build the interconnection and interoperability of a physical shop floor and corresponding cybershop floor. A Digital Twin-based Cyber-Physical Production System (DT-CPPS) is further established, and the configuring mechanism, operating mechanism and real-time data-driven operations control of DT-CPPS are discussed in detail. It is expected that DT-CPPS will provide the basis for shop floors to march towards smart manufacturing.

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Section: Cps/cpps and Autonomous Manufacturingmentioning

confidence: 99%

Defining a Digital Twin-based Cyber-Physical Production System for autonomous manufacturing in smart shop floors

Ding

Chan

Zhang

et al. 2019

International Journal of Production Research

328

106

View full text Add to dashboard Cite

show abstract

“…For successful status monitoring, MES need to meet the following conditions: first, a factory must be digitized and synchronized with networks to respond to actual situation changes in real time [75]. Second, three levels of enterprise management, production management and production must be vertically integrated via automation.…”

Section: Status Monitoring and Predictive Maintenancementioning

confidence: 99%

Green Production Planning and Control for the Textile Industry by Using Mathematical Programming and Industry 4.0 Techniques

Tsai

2018

Energies

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Abstract:The textile industry is one of the world's major sources of industrial pollution, and related environmental issues are becoming an ever greater concern. This paper considers the environmental issues of carbon emissions, energy recycling, and waste reuse, and uses a mathematical programming model with Activity-Based Costing (ABC) and the Theory of Constraints (TOC) to achieve profit maximization. This paper discusses the combination of mathematical programming and Industry 4.0 techniques to achieve the purpose of green production planning and control for the textile industry in the new era. The mathematical programming model is used to determine the optimal product mix under various production constraints, while Industry 4.0 techniques are used to control the production progress to achieve the planning targets. With the help of an Industry 4.0 real-time sensor and detection system, it can achieve the purposes of recycling waste, reducing carbon emission, saving energy and cost, and finally achieving a maximization of profit. The main contributions of this research are using mathematical programming approach to formulate the decision model with ABC cost data and TOC constraints for the textile companies and clarifying the relation between mathematical programming models and Industry 4.0 techniques. Managers in the textile companies can apply this decision model to achieve the optimal product-mix under various constraints and to evaluate the effect on profit of carbon emissions, energy recycling, waste reuse, and material quantity discount.

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“…The upper limit here is 0.6 as any higher values lead to the light ray not reaching the other side of the domain, i.e. having an end co-ordinate as (1.5, ) y m with [ 2,2]. y ∈ − Figure 4 shows the 25 rays propagating in the geometry.…”

Section: Setting Up the Simulation In Comsolmentioning

confidence: 99%

“…As the world enters the fourth industrial revolution, the autonomous age, automated systems are being increasingly used for component positioning and assembly [1]. Industries are interested in autonomous and robotic manufacturing as it potentially reduces costs and increases productivity [2]. The robots used in large volume manufacturing need to know their own spatial position in the working volume and the spatial position of the object that they are working on.…”

Section: Introductionmentioning

confidence: 99%

Positional uncertainty in optical-based metrology systems in large volume manufacturing

et al. 2018

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<p class="Abstract"><span lang="EN-US">Modern manufacturing increasingly utilizes automated systems for component positioning and assembly and a vital aspect of autonomous precision manufacturing is large volume metrology. One popular approach uses light rays, which travel through the volume of air, to calculate the position of an object of interest. These optical-based metrology systems such as photogrammetry and laser tracking are crucial in improving the accuracy and quality associated with robotic assembly. However, in an industrial setting, these positional measurement systems give rise to uncertainties which can in many instances be greater than the required tolerances. One source of this uncertainty is light refraction due (in part) to temperature fluctuations in the air. This paper will describe how COMSOL Multiphysics can be used to create simulated data with complete ground truth on the refractive index field in the volume, and will discuss the measurement uncertainties associated with these simulations. Over industry relevant distances (tens of metres) the uncertainty in the position measurement due to light refraction is of the order of a millimetre.</span></p>

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An autonomous manufacturing system for adapting to disturbances

Cited by 19 publications

References 7 publications

Defining a Digital Twin-based Cyber-Physical Production System for autonomous manufacturing in smart shop floors

Defining a Digital Twin-based Cyber-Physical Production System for autonomous manufacturing in smart shop floors

Green Production Planning and Control for the Textile Industry by Using Mathematical Programming and Industry 4.0 Techniques

Positional uncertainty in optical-based metrology systems in large volume manufacturing

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