A framework of energy consumption modelling for additive manufacturing using Internet of Things

The topic of ‘Industry 4.0’ has become increasingly popular in manufacturing and academia since it was first published. Under this trending topic, researchers and companies have pointed out many related capabilities required by current manufacturing systems, such as automation, interoperability, consciousness, and intelligence. Additive manufacturing (AM) is one of the most popular applications of Industry 4.0. Although AM systems tend to become increasingly automated and worry less, the issue of energy consumption still attracts attention, even in the Industry 4.0 era, and is related to many processing factors depending on different types of AM system. Therefore, defining the energy consumption behaviour and discovering more efficient usage methods in AM processes is established as being one of the most important research targets. In this paper, an Internet of Things (IoT) framework is designed for understanding and reducing the energy consumption of AM processes. A huge number and variety of real-time raw data are collected from the manufacturing system; this data is analysed by data analytical technologies, combining the material attributes parameter and design information. This data is uploaded to the cloud where more data will be integrated for discovering the energy consumption knowledge of AM systems. In addition, a case study is also presented in this paper, which a typical AM system is focused on the target system (EOS P700). The raw data is collected and analysed from this process. Then, based on the IoT framework, a novel energy consumption analysis proposal is proposed for this system specifically

An approach to the characterisation of the performance of a tidal stream turbine

In order to better manage and maintain deployed Tidal Stream Turbine (TST) devices their response to complicated and severe loading mechanisms must be established. To aid this process the research presented details a methodology for mapping TST operational data, taken under a variety of operating conditions, to a set of model parameters. The parameter sets were developed based on a TST rotor torque model which, as well as providing means of characterising turbine behaviour, can be used to create TST simulations with minimal computation expense. The use of the model in facilitating parameter surface mapping is demonstrated via its application to a set of rotor torque measurements made of a 1/20th scale TST during flume testing. This model is then deployed to recreate the known rotor behaviour which is compared with the original flume based measurements. This is a flexible tool that can be applied to investigate turbine performance under conditions that cannot be readily replicated using tank-based experiments. Furthermore, Computational Fluid Dynamics simulations of such conditions could be time consuming and computationally expensive. To this end, the use of the model in creating drivetrain test bed based simulations is demonstrated. The model, which can be calculated in real-time, is used to develop representative turbine simulations at high turbulence intensity levels which were not achievable during flume experimentation. The intention is to provide a test-bed for future turbine performance monitoring under more realistic, site specific conditions. The work will also support the deployment of performance surfaces in real-life turbine applications

Assessing uneven milling cutting tool wear using component measurement

Tool wear is a complex phenomenon inherent in any cutting process. Cutting tool wear monitoring is therefore deployed in CNC milling to support machining operations in order to plan tool changes and avoid economic losses. The application of tool life management strategies can lead to premature removal of healthy tool or the continued use of a dangerously worn tool. This has led to the investigation of more appropriate strategies. Depending upon the nature of the sensor technology deployed tool wear monitoring methods are categorized as being either direct or indirect. The benefits and challenges to machine tool users of both approaches are subject to a body of ongoing research. In this study, a series of milling machining tests were performed in order to allow the confirmation of the presence of uneven tool flank wear. This was enabled by the indirect assessment of the tool condition by utilising a Coordinate Measurement Machine (CMM) to accurately measure the workpieces. Using a defined machining process with set cutting parameters each workpiece was machined to produce eight off 40 mm cylindrical holes; in this manner using four workpieces a series of 32 holes were machined. Each cylinder was machined using four separate cuts, at increasing depths, producing four identifiable sections. Each section was measured and the form of the geometry produced was established. After assessing the diameters of all the sections for each cylinder, the presence of uneven flank wear was confirmed and the levels obtained. This is related directly to the differing amount of metal removed by the cutter during the established cutting cycle. The same processes was undertaken using three different sets of cutting parameters. The analysis showed the CMM to be a reliable basis for the measurement of uneven tool wear based upon the geometry of the component

A new insight into modelling passive suspension real test rig system with consideration of nonlinear friction forces

The vital purpose of a vehicle suspension system is to isolate the car body and hence passengers, from roadway unevenness disturbances. Implementation of passive suspension systems has continuously improved disconnection from disturbances through available deflection constraints to provide maximum isolation. In the majority of relevant reported research studies, a quarter car is modelled as moving vertically straight for both a viscous damper and a stiffness spring. The motivation for this study, reported here, is to extend the modelling to take account of the actual configuration of a test rig system. Accordingly, a new passive suspension system model is presented, which includes nonlinear lubricant friction forces that affect the linear support body bearings. The friction model established relies on dynamic system analysis and the fact of slipping body on lubricant bearings; this model captures most of the friction behaviours that have been observed experimentally. The suspension model is composed of a car body and wheel unit, and only vertical motion (bounce mode) is addressed. In addition, an active actuator is used to generate the system inputs as a road simulator. Therefore, a nonlinear hydraulic actuator, including the dynamic of servovalve and proportional–integral controller model, is established. This study is validated by experimental work, with simulations achieving C++compiler. As a result, a good agreement is obtained between the experimental and simulation results, that is, the passive suspension system with considered nonlinear friction and the nonlinear hydraulic actuator with servovalve equation models are entirely accurate and useful. The suggested proportional–integral controller successfully derives the hydraulic actuator to validate the control scheme. The ride comfort and handling response are close to that expected for the passive suspension system with road disturbances

The specification and testing of a horizontal axis tidal turbine rotor monitoring approach.

The sustainable deployment of Horizontal Axis Tidal Turbines will require effective management and maintenance functions. In part, these can be supported by the engineering of suitable condition monitoring systems. The development of such a system is inevitably challenging, particularly given the present limited level of operational data associated with installed turbines during fault onset. To mitigate this limitation,a computational fluid dynamics model is used to simulate the operational response of a turbine under a known set of fault conditions. Turbine rotor imbalance faults were simulated by the introduction of increasing levels of pitch angle offset for a single turbine blade. The effects of these fault cases upon cyclic variations in the torque developed by the turbine rotor were then used to aid creation of a condition monitoring approach. A parametric tidal turbine rotor model was developed based on the outputs of the computational fluid dynamics models. The model was used to facilitate testing of the condition monitoring approach under a variety of more realistic conditions. The condition monitoring approach showed good performance in fault detection and diagnosis for simulations relating to turbulence intensities of up to 2 %. Finally,the condition monitoring approach was applied to simulations of 10 % turbulence intensity. Under the 10 % turbulence intensity case the rotor monitoring approach was successfully demonstrated in its use for fault detection. The paper closes with discussion of the effectiveness of using computational fluid dynamics simulations extended by parametric models to develop condition monitoring systems for horizontal axis tidal turbine applications

CNC spindle signal investigation for the prediction of cutting tool health

The deterioration of cutting tools plays a significant role in the progression of subtractive manufacturing and substantially affects the quality of machined parts. Recognising this most organisations have implemented conventional methods for tool management. These reduce the economic loss associated with time-dependent and stochastic tool wear, and limit the damage arising from tools at end-of-life. However, significant costs still remain to be addressed and more development towards tool and process prognostics is desirable. In response, this work investigates process deterioration through the acquisition and processing of selected machine signals. This utilises the internal processor of a CNC Vertical Machining Centre and considers the possible applications of such an approach for the prediction of tool and process health. This paper considers the prediction of tool and process condition with a discussion of the assumptions, benefits, and limitations of such approaches. Furthermore, the efficacy of the approach is tested using the correlation between an offline measurement of part accuracy and an active measure of process variation

The difficulties of the assessment of tool life in CNC milling

In the manufacturing process, tool life is an important parameter in milling operations. The main objective of this paper is to explain how difficult is it to assess how much work a tool has undertaken before it must be changed. A number of ways of expressing tool life are currently used, including the conventional method based upon one of several configurations of the Taylor Tool Life Equation. These usually express tool life in terms of known material properties together with primary machining variables like speed, feed and depth of cut. Other approaches are based upon the extrapolation of a tool wear curve and considerations of the volume of metal removed. This initial investigation adopts an approach that is based upon a series of experiments, which produce data indicating the changes in machined feature form and dimension. For this study, a new test piece was designed in order to allow the indirect assessment of the tool flank wear by utilising a Coordinate Measuring Machine to accurately measure the workpieces. This work is intended to indicate how difficult it is to actually apply the existing methods to manage tool wear. The aim is to engineer a better way and to establish a methodology of measuring what the tool is actually doing in real time using the machine controller

An initial characterisation of a tidal stream turbine on a drive train test rig

The potential of tidal stream turbines simulations on steady-state conditions by the use of a drive train test rig is considered. An initial assessment of two case scenarios is developed to furtherly assess the availability of replicating a theoretical model to the experimental model. It has been demonstrated that a drive train test rig is able to represent power curves of a 0.5 m diameter turbine with velocities from 0.5 to 1.8 ms-1 given its torque value and its rotational frequency. IndraWorks Engineering is being used to obtain the rotor and generator signals and review the losses through a horizontal axis tidal turbine drivetrain. This provides a first order approximation for the use of the test rig with non-steady state conditions and develop condition monitoring techniques