Optimal design of a frictional pair of a hub–plunger

Based on the model of a rough friction surface, the theoretical analysis of the displacement function for the external contour points of the hub of a frictional pair, providing the absence of the initial wear and tear, which takes place towards the end of the bedding period, is carried out. The obtained displacement function for the external contour points of the hub provides increased wear resistance of the frictional pair.     

Driving shaft fatigue optimization design of Ω type profile twin-screw pumps

Under changeable pumped medium and working environment, the twin-screw pump is prone to be broken by fatigue failures. A structure optimization design model and method of the driving shaft are presented based on response surface methodology and finite element analysis. In this model, the shaft diameter, chamfering degree and the shaft extension of the power end are selected as optimization variables, the limit values of the variables and maximal normal deformation of the spindle are considered as the constraint conditions, and the minimization of the equivalent alternating stress on the dangerous shaft section is taken as the optimization objective so as to improve the shaft fatigue reliability. The optimization results of a case show that the equivalent alternating stress on the dangerous spindle section reduces by 26.2 %, and the maximal normal deformation decreases by 25.2 % compared with the original design. In addition, the infinite life reliability and fatigue safety factors both meet the design requirements.     

Multi-objective optimization design of a fixture layout considering locator displacement and force–deformation

The fixture determines the workpiece position in a machining process; therefore, an increasing amount of attention has been given to fixture layout design. While machining, the workpiece position is affected by two major sources: (a) the locator displacement and (b) the force–deformation of the workpiece–fixture system. In the beginning of this paper, a geometric model considering the shape of a locator is developed to analyze the location performance, followed by the presentation of a simplified solving method and a location layout performance index. Second, to complete the force–deformation analysis, a finite element method-based force–deformation model is built and accelerated by a new method with a lower computer memory cost. Based on these two models, multiple objects of fixture layout optimization problems are proposed, and a multi-objective genetic algorithm-based optimization method is constructed. Finally, testing examples are approved to examine the validity of the method represented in this paper. These methods can provide a more accurate prediction of the locating performance in more widely used cases, and they have faster calculating speeds with lower computer memory costs.     

Optimization design of a CUSUM control chart based on taguchi’s loss function

The CUSUM charts have been widely used in statistical process control (SPC) across industries for monitoring process shifts and supporting online measurement and distributed computing. This paper proposes an algorithm for the optimimal design of a CUSUM control chart detecting process shifts in the mean value. The algorithm optimizes the sample size, sampling interval, control limit and reference parameter of the CUSUM chart through minimizing the overall mean value (ML) of a Taguchi’s loss function over the probability distribution of the random process mean shift. A new feature related to the exponential of the sample mean shift is elaborated. Comparative studies reveal that the proposed ML-CUSUM chart is considerably superior to the Shewhart ML- $\overline{X} $ chart and the conventional CUSUM chart in terms of the overall loss of ML.     

Reliability-based design optimization of a pick-up device of a manganese nodule pilot mining robot using the Coandă effect

Design of a pick-up device using the Coandă effect in a deep-sea mining robot is vital to develop a reliable and sustainable deep-sea mining system. One of the crucial performance metrics of this device is the collection efficiency since it affects the mining efficiency of the entire system. However, the collection efficiency is significantly affected by the uncertainties of shape, size and mass of manganese nodules on the seabed. In this study, reliability-based design optimization (RBDO) was performed to improve the reliability of the collection efficiency of the pick-up device under these environmental uncertainties. First, a computational model based on the Coandă effect that predicts the collection efficiency of the pick-up device was developed. Next, RBDO based on the Akaike information criterion method was employed to design the pick-up device by using this model. The results demonstrated that the proposed design methodology significantly improved the design of the pick-up device for the pilot mining robot.

     

A new design method for PI–PD control of unstable processes with dead time

PID controllers are still widely practiced in the industrial systems. In the literature, many publications can be found considering PID controller design for unstable processes. However, owing to the structural limitations of PID controllers, generally, good closed loop performance cannot be achieved with a PID for controlling unstable processes and usually a step response with a high overshoot and oscillation is obtained. On the other hand, PI–PD controllers are proved to give very satisfactory closed loop performances for unstable processes. The paper presents a simple design method to tune parameters of a PI–PD controller for the control of the unstable processes with time delay. The proposed method is based on plotting the stability boundary locus, which is a locus dependent on the parameters of the controller and frequency, in the parameter plane. The method uses a new concept named centroid of the convex stability region. Simulation examples and an experimental application are given to illustrate the superiority of the proposed method over some existing ones.     

A multi-echelon reverse logistics network design for product recovery—a case of truck tire remanufacturing

Due to increasing environmental deterioration, government regulations, social responsibilities, resource reduction, and economic factors, many companies are engaged in the product recovery business. Product recovery refers to the set of activities designed to reclaim value from a product at the end of its useful life. Due to the increasing number of vehicles in the country like India, large quantities of used tires are generated every year, and proper disposal of these used tires creates a significant problem in the day-to-day life. An alternative way to recover the value (tire remanufacturing also called retreading) from the used tire is proposed in this work. The implementation of such remanufacturing system usually requires an appropriate reverse logistics network for choosing the physical locations, facilities, and transportation links to convey the used products from customers to the remanufacturing facility and from there to secondary markets. The main objective of this work is to develop a mixed integer nonlinear programming model for maximizing the profit of a multi-echelon reverse logistics network and also to present a real-life case study of truck tire remanufacturing for the secondary market segment. The proposed model is solved using LINGO 8.0 optimization solver which provides the decisions related to the number of facilities to open, their locations, and also the allocation of the corresponding product flows. Finally, it is concluded that the choice of using retreaded tires is a profitable one by the way of cost reduction. Sensitivity analysis of the model is also presented to find the maximum allowable distance between the customers and initial collection points.     

Influence of steam injection through exhaust heat recovery on the design performance of solid oxide fuel cell — gas turbine hybrid systems

This study analyzed the influence of steam injection on the performance of hybrid systems combining a solid oxide fuel cell and a gas turbine. Two different configurations (pressurized system and ambient pressure system) were examined and the effects of injecting steam, generated by recovering heat from the exhaust gas, on system performances were compared. Performance variations according to the design of different turbine inlet temperatures were examined. Two representative gas turbine pressure ratios were used. Without steam injection, the pressurized system generally exhibits higher system efficiency than the ambient pressure system. The steam injection augments gas turbine power, thus increasing the power capacity of the hybrid system. The power boost effect due to the steam injection is generally greater in the relatively higher pressure ratio design in both the pressurized and ambient pressure systems. The effect of the steam injection on system efficiency varies depending on system configurations and design conditions. The pressurized system hardly takes advantage of the steam injection in terms of system efficiency. On the other hand, the steam injection contributes to the efficiency improvement of the ambient pressure system in some design conditions. In particular, a higher pressure ratio provides a better chance of efficiency increase due to the steam injection. This paper was recommended for publication in revised form by Associate Editor Kyoung Doug Min Mr. S. K. Park received his MS degree from Dept of Mechanical Engineering, Inha University in 2007, and is now Doctoral student at the same department. His research topics include performance analysis of fuel cell and fuel cell/gas turbine hybrid sys-tem and advanced energy systems. Prof. T. S. Kim received his PhD degree from Dept of Mechanical Engineering, Seoul National University in 1995. He has been with Dept of Mehanical Engineering, Inha University since 2000, and is Associate Professor as of Nov. 2008. His research area includes simulation and test of gas turbines and aerodynamic performance of their components. He is also interested in researches on fuel cells and fuel cell/gas turbine hybrid systems. Prof. J. L. Sohn received his PhD degree from Dept of Mechanical Engineering, The University of Alabama in Huntsville in 1986. He has been with School of Mechanical & Aerospace Engineering, Seoul National University since 2000, and is BK Associate Proessor as of Nov. 2008. His research area is design, simulation and test of gas turbine system and components. He is also interested in researches on fuel cells and fuel cell/gas turbine hybrid systems.     

FuncDesigner—a functional design software system

Engineering design focuses on the development of products and artefacts to satisfy the specified function. Although considerable advances have been made over the last two decades in functional modelling, there is not very much progress on commercial Computer-Aided Design (CAD) systems that really aid the designer in converting functional specifications to concept variants. Based on our previous work on Behaviour-driven Function-Environment-Structure (B-FES) modelling framework, this paper presents a functional design software system, called "FuncDesigner", to support the functional design of mechanical products through functional reasoning steps, including causal behavioural reasoning and functional decomposition. A function object library and a behaviour object library have been developed as well to serve as the knowledge base for the computerised functional modelling environment. The proposed functional design software system has been evaluated with a design example of a terminal insertion unit in an automatic assembly system for manufacturing electronic connectors.     

Springback prediction of high-strength sheet metal under air bending forming and tool design based on GA�CBPNN

Based on orthogonal test for air bending of high-strength steel sheets, 125 values of sheet thickness (t), tool gap (c), punch radius (r), ratio of yield strength to Young??s modulus (?? _y /E), and punch displacement (e) are used to model the springback for air bending of high-strength sheet metal using the genetic algorithm (GA) and back propagation neural network (BPNN) approach, where the positive model and reverse model of springback prediction are established, respectively, with GA and BPNN. Adopting the ??object-positive model?Creverse model?? learning method, air bending springback law is studied with positive model and punch radius is predicted by reverse model. Manifested by the experiment for air bending forming of a workpiece used as crane boom, the prediction method proposed yields satisfactory effect in sheet metal air bending forming and punch design.     

Tool fabrication system for micro/nano milling—function analysis and design of a six-axis Wire EDM machine

The dies or molds used for the fabrication of micro products usually are made of ultra-hard materials such as tungsten carbide or silicon carbide and have sophisticated three-dimensional geometries. Such kind of dies or molds can only be fabricated by milling operations instead of grinding processes with ultra-hard milling tools made of PCD or CBN. Electrical discharge machining (EDM) is a good choice for the fabrication of such ultra-hard tools. In this paper, a function analysis and design of a six-axis Wire EDM (WEDM) machine is introduced. Based on the typical micro/nano cutting tool geometry features, a mathematical model between the cutting tool and the electrode wire is built. Then, the mathematical model is analyzed and it turns out that six axes are needed for cutting such complicated tool geometries. According to the WEDM features, first the axes are allocated to the workpiece side and the electrode wire side. The workpiece is assigned three linear motions and one rotary motion around its center line and the wire has two rotary motions. Second, the axis sequences are defined. At last, the best concept of the mechanical structure for the six-axis WEDM machine is selected.     

Analysis,control and design of a non-inverting buck-boost converter: A bump-less two-level T–S fuzzy PI control

In this paper, a new modified fuzzy Two-Level Control Scheme (TLCS) is proposed to control a non-inverting buck-boost converter. Each level of fuzzy TLCS consists of a tuned fuzzy PI controller. In addition, a Takagi–Sugeno–Kang (TSK) fuzzy switch proposed to transfer the fuzzy PI controllers to each other in the control system. The major difficulty in designing fuzzy TLCS which degrades its performance is emerging unwanted drastic oscillations in the converter output voltage during replacing the controllers. Thereby, the fuzzy PI controllers in each level of TLCS structure are modified to eliminate these oscillations and improve the system performance. Some simulations and digital signal processor based experiments are conducted on a non-inverting buck-boost converter to support the effectiveness of the proposed TLCS in controlling the converter output voltage.     

Disc cutters’ layout design of the full-face rock tunnel boring machine (TBM) using a cooperative coevolutionary algorithm

In rock TBM design the disc cutters’ layout design of the full-face rock tunnel boring machine (TBM) is one of the key technologies. However, there are few published papers in literatures for various reasons. In this paper, based on the engineering technical requirements and the corresponding cutter head’s structure design requirements, a nonlinear multi-objective disc cutters’ layout mathematical model with complex constraints and the corresponding multi-stage solution strategy are presented, in which the whole disc cutters’ layout design process is decomposed into the disc cutters’ spacing design and the disc cutters’ plane layout design. A numerical simulation method based on the FEM theory is adopted to simulate the rock chipping process induced by three TBM disc cutters to determine the optimal cutter spacing. And a cooperative coevolutionary genetic algorithm (CCGA) is adopted to solve the disc cutters’ plane layout design problem. Finally, a disc cutters’ layout design instance of the TBM is presented to demonstrate the feasibility and effectiveness of the proposed method. The computational results show that the proposed method can be used to solve the disc cutters’ layout design problem of the TBM and provide various layout schemes within short running times for the engineers to choose from.     

RETRACTED ARTICLE: Composition design and mechanical properties of BCC Ti solid solution alloys with low Young’s modulus

(Ti-Zr)-Mo-Nb alloys were studied to find some stabilized BCC solid solution with low Young’s Modulus. We propose a cluster-plusglue-atom model to solve the composition design of multi-component complex alloys from the structure viewpoint. The alloy composition is expressed with [cluster](glue atom)x according to the model, x denoting the number of glue atoms matching one cluster. Alloy structures were identified with XRD and optical microscopy (OM), and mechanical tests were finally carried on to the BCC alloys. The experimental results indicated that a series of β-Ti solid solution alloys with low Young’s modulus and good synthesized mechanical properties can be obtained with the cluster model, where the [CN14 cluster](glue)1 alloys given by of 1:1 cluster model have the optimum properties.     

Dynamic cellular manufacturing systems design��a comprehensive model

This paper addresses the dynamic cell formation problem (DCF). In dynamic environment, the product demand and mix changes in each period of a multiperiod planning horizon. It causes need of reconfiguration of cells to respond to the product demand and mix change in each period. This paper proposes a mixed-integer nonlinear programming model to design the dynamic cellular manufacturing systems (DCMSs) under dynamic environment. The proposed model, to the best of the author??s knowledge, is the most comprehensive model to date with more integrated approach to the DCMSs. The proposed DCMS model integrates concurrently the important manufacturing attributes in existing models in a single model such as machine breakdown effect in terms of machine repair cost effect and production time loss cost effect to incorporate reliability modeling; production planning in terms of part inventory holding, part internal production cost, and part outsourcing; process batch size; transfer batch size for intracell travel; transfer batch size for intercell travel; lot splitting; alternative process plan, and routing and sequence of operation; multiple copies of identical copies; machine capacity, cutting tooling requirements, work load balancing, and machine in different cells constraint; machine in same cell constraint; and machine procurements and multiple period dynamic cell reconfiguration. Further, the objective of the proposed model is to minimize the sum of various costs such as intracell movement costs; intercell movement costs and machine procurement costs; setup cost; cutting tool consumption costs; machine operation costs; production planning-related costs such as internal part production cost, part holding costs, and subcontracting costs; system reconfiguration costs; and machine breakdown repair cost, production time loss cost due to machine breakdown, machine maintenance overheads, etc. ,in an integrated manner. Nonlinear terms of objective functions are transformed into linear terms to make mixed-integer linear programming model. The proposed model has been demonstrated with several problems, and results have been presented accordingly.     

Multi-response design of Nd:YAG laser drilling of Ni-based superalloy sheets using Taguchi��s quality loss function, multivariate statistical methods and artificial intelligence

This paper presents a hybrid design strategy for the determination of the optimum laser drilling parameters which simultaneously meets the requirements for seven quality characteristics (responses) of the holes produced during pulsed Nd:YAG laser drilling of a thin sheet of nickel-based superalloy Nimonic 263. The process was designed using two approaches based on the experimental data. In the first approach, the quality losses of seven correlated responses were uncorrelated into a set of components using the principal component analysis; then the grey relational analysis was applied to synthesise components into a synthetic performance measure. Since this approach considered only parameter values used in the experiment, the second approach was developed to find the global optimal parameters solution using an artificial neural network to model the relation between parameters and a synthetic performance measure, and a genetic algorithm to perform a search for the global optimum in a continual multidimensional space. The analysis of the application indicated that the proposed approaches gave a better result, in terms of the optimal parameter settings that yield the maximal synthetic performance measure, than several commonly used methods for multi-response process parameters design. The results demonstrated that the robust Nd:YAG laser drilling of Ni-based superalloy sheets was designed with respect to the requirements for seven quality characteristics of the drilled holes, by using the proposed strategy.