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This purpose of this research work primarily focuses on assessing the contact characteristics of a novel 3D printed flexible poly lactic acid (PLA) fingertip exposed to a normal load ranging from 1–750 N. The 3D printed fingertip is pressed against three different target surfaces having concave, convex and flat profiles to facilitate a rational comparison. The growth of contact area is recorded for a wide range of applied normal force against the fingertip on logging sheets and the same is converted in vector format for facilitating digital measurements. From close examination of the results, it may be noted that the rate of growth of contact area follows the parametric relationship a = cN γ . A weighted least squares fit algorithm is used to formulate the parametric relationship based on experimental data. Further, the contact characteristics of the 3D printed fingertip follows the same pattern of soft neoprene fingertip, and it is well in line with the expected results. Hence, it is evident that 3D printed fingertips could be utilized for handling fragile to hard objects and capable of handling multi-profiled objects in dexterous robotic manipulation. Moreover, complex profiled fingertips can easily be manufactured by 3D printing, and it can be considered as a better alternative for conventionally manufactured anthropomorphic robotic grippers. Practical implications of this research will be highly useful for development of soft-fingered robotic grippers for dexterous robotic manipulations.

Road safety and its risk assessment has become very significant due to the increasing population and usage of transports in the current scenario. This research work primarily focuses on assessing the critical risk factors that trigger road accidents in India. Based on literature review and expert’s opinion, twenty-eight risk factors are identified and rated on a scale from 1 – 6. These critical factors are prepared as a questionnaire and the required input data is collected from a diversified set of automotive users. Further, the data is carefully processed and analyzed for identification of severe risk factors and its allied route cause based on the survey pattern. Three different cut-off patterns (Low risk, high risk & medium risk zone) are included to make the study more interesting, and the 28 factors are clustered with the aid of the collective results. Also, the dominant risk factors that has higher probability in triggering road accidents are identified for possible rectification.

Determining the optimum cutting tool positions in a tool magazine is a challenging task which involves a huge searching space. Reduction of manufacturing time even by nanoseconds will highly be beneficial for all process industries. The prime focus of this research work is to reduce the total turret or tool indexing time in Automatic Tool Changer (ATC) which in turn curtails the idle non-cutting time of the bi-directional turret or tool magazine in a CNC machine. This variant of optimization problem falls under the category of non-deterministic hard polynomial (NP-hard) problem. Chemical Reaction Optimization (CRO) algorithm is proposed to determine the near optimal/global optimal solution with lesser computational cost. Five benchmark case studies are considered in this work to assess the robustness of the proposed algorithm. From the results, it is evident that the proposed algorithm yields solutions which matches or exceeds with the solution quality.

In recent decades, modeling of soft fingertips has fascinated a superior momentum in research initiatives concerned with development of an anthropomorphic soft finger tip. In design and development of soft fingertips, analysis of contact a characteristic plays a vital role on dexterous manipulation. This research work presents the results of the experimental investigation in relation to the formulations of contact area for soft fingertips pressed against assorted target profiles. A dimensionless parameter, curve factor Y (r/R) is introduced to derive a parametric relationship among the key parameters. It also addresses the growth of contact area of fingertips for five different combinations. From experimental observations, a modified power law equation with conversion factor (X) is proposed to interpolate the magnitude of contact area for different profiles.

In recent decades, research on soft robot manipulations and their materials attracted a huge momentum among various researchers. Selection of appropriate soft material is a vital role in robotic fingertip design, which enables the object to be held in proper orientation without slip and damage. Development of such an anthropomorphic type of soft hand requires knowledge about material selection, types of finger contact and the mechanism behind grasping. This research work presents a comprehensive comparison of six chosen soft materials with human skin for improved robotic manipulation. Extensive research is required to develop such soft hands for better manipulation becausein the final analysis, the human hand is the best soft manipulator as it conforms to objects easily through good contact with an object. In the past decades, many researchers have tried to replace metal hand of robots with appropriate soft materials to enable better manipulation. In this work, the magnitude of contact area, contact pressure and vertical depression of six soft materials was compared with human skin with respect to precision grasping. The simulation results clearly show that neoprene rubber exhibits a close relationship with the characteristics of human skin.

The prime objective of this research work is focused on assessing the dynamic characteristics of a multi core sandwich composite beam with cutouts.The effect of introducing additional cores in sandwich beams is investigated in detail along with various geometric configurations. Also, the impact of placing multiple cutouts with assorted geometric profiles (Circular, Square, Hexagon and Triangular) in a sandwich structure is also addressed in detail. Finite element technique is deployed for numerical analysis and parametric studies. In addition, the influence of reinforcements in the proposed structure is also presented. From the results, it is evident that square cutouts possess the highest damping capability irrespective of geometric position of its placement. Also, it may be concluded that the geometric position of placing cutoutssignificantly influences the magnitude of frequency levels ranging to maximum of 42% hike at lower modes.Moreover, introduction of cutouts leads to reduction in frequency levels for all the cases up to 20%. Furthermore, secondary investigation of multicore reinforced sandwich beams experiences a maximum reduction in frequency of about 15%.

This paper presents a finite element study on the contact parameters of a soft hemispherical finger tip pressed against curved surface. The variation in magnitudes of contact radius, contact pressure and vertical displacement are estimated using two-dimensional finite element models. The special effects of geometry using a wide range of normal force on soft finger tips are presented with the aid of a dimensionless parameter, curve factor (R/a). It addresses the effects of the load–contact relationship for ten different fingertip combinations. From close observations it can be concluded that a higher magnitude of contact radius can be obtained with a lower curve factor and vice-versa. Also, it is evident that the radius of contact is higher for a curved object when compared with a flat one for a particular combination. However, there is a significant reduction in the magnitudes of vertical depression and contact pressure.

The bio-mechanics of skin and bone play a crucial role in dexterous object manipulations and artificial robotic gripper design. Establishing a quantitative relationship between imposed loads and contact factors is necessary to understand the governing mechanics behind it. Towards this goal, experimental investigations on the contact parameters of a sandwich soft fingertip comprising a soft layer and solid core are presented. The influence of soft layer stratum and material grades on the power law equation is investigated by introducing a new dimensionless parameter – Power Factor. The results clearly indicate that the power index “γ” is dependent on the material as well as shell thickness and in addition the proportionality constant “C” is dependent on the geometry. Also, the magnitude of both the constants increases with power factor and saturates at a value of ≈1.25. Numerical simulation is performed to support the experimental results. Finally, an optimum ratio of power factor is determined and the number ≈1.25 is critical in designing the artificial robotic sandwich fingertip.

The main purpose of the present work is to develop an artificial fingertip comprised of a soft layer and an inner rigid core, which emulates a human one with skin and bone. The influences of introducing the core and the effects of variations in thickness of the soft layer over the contact parameters are investigated. From the results, it is evident that the power law theory proposed by (Xydas N, Kao I. Int. J. Rob. Res. 1999, 18, 941–950) becomes invalid in this criterion; by contrast, if the power law theory acts for finger tips with internal cores, the conclusion may be redefined in such a way that the soft material behaves more softly in the presence of internal cores and the dimensionless number, core-soft layer coefficient Fcs≈0.5, is the critical parameter which produces the change of behavior. Moreover, soft finger tips with an inner core are preferable to entirely soft ones, as a higher grasping stability is achieved with the same area of contact, and the conforming nature of the fingers is maintained.

This work aims at estimating and comparing the frequency and loss factor of a mild steel sandwich shaft disc system containing viscoelastic, electro-rheological fluid (ERF), and magneto-rheological fluid (MRF) core materials with mild steel as the facing layers. Because the structure is axisymmetric, a semi-analytical finite element method was implemented to study the frequency and loss factor values of the mild steel sandwich shaft disc system. The effects of an electric field for the ERF material and a magnetic field for the MRF material on the vibration behavior of the mild steel sandwich shaft disc system were studied. A quantitative study identified the combination of mild steel facing with a viscoelastic core shaft disc system that produced the highest frequency and loss factor values. In addition, the effect of an electric field and a magnetic field on ERF and MRF core improves the damping performance of the structure.

The main aim of this paper is to investigate the effect of various constrained layers (viscoelastic layer (VEL), electro-rheological fluid (ERF), and magneto-rheological fluid (MRF)) over natural fre- quency and the damping loss factor with two different fiber orientations (0 and 90) for a Graphite/Epoxy (GR/E) composite sandwich shaft disc system. The finite element technique is used to investigate the natural frequency and loss factor for various combina- tions. Furthermore, the vibrational characteristics of the composite sandwich shaft disc system are compared with those of the base structure without constrained layers. The study shows that introducing various constrained layers reduces the magnitude of natural frequency by up to 80%. The results also show that GR/ E composite with 90 fiber orientation acquires the highest frequency reduction. Among the proposed layers, VEL has the highest damping loss factor.

Modeling of soft finger contact mechanics is a prerequisite for gripper design. Realism of soft finger deformations depends extremely on the selection of appropriate hyper-elastic material model for soft materials. The essential criterion for a good mathematical model for hyper elasticity is its ability to match the measured strain energy curves under different deformations over a large range. Selecting an appropriate material law for a given material combination is one of the most difficult tasks in soft finger contact modeling. The present study is devoted for comparing seven popular hyper-elastic non-linear material models (Mooney–Rivlin, Ogden, Yeoh, Neo-Hookean, Gent, Polynomial and Aruda–Boyce model) and selection of the most appropriate model based on experimental data for modeling of soft contact problems. Present results clearly reveal that Ogden and Neo-Hookean model are more suitable for these problems and in line with the experimental results. Finite element technique is employed for critical comparison of various hyper-elastic material models.

Computer-aided process planning (CAPP) is an important interface between computer-aided design (CAD) and computer-aided manufacturing (CAM) in computer-integrated manufacturing environment. A problem in traditional CAPP system is that the multiple planning tasks are treated in a linear approach. This leads to an over constrained overall solution space and the final solution is normally far from optimal or even non-feasible. The operation-sequencing problem in process planning is considered to produce a part with the objective of minimizing the sum of machine, setup and tool change costs. In general, the problem has combinatorial characteristics and complex precedence relations, which makes the problem more difficult to solve. In this paper, the feasible sequences of operations are generated based on the precedence cost matrix and reward–penalty matrix using simulated annealing technique (SAT), a meta-heuristic. A number of benchmark case studies are carried out to demonstrate the feasibility and robustness of the proposed algorithm. This algorithm performs well on all the test problems, exceeding or matching the solution quality of the results reported in the literature for most problems. The main contribution of this work focuses on reducing the optimal cost with a lesser computational time along with generation of more alternate optimal feasible sequences. The proposed SAT integrates robustness, convergence and trapping out of local minima.

A new hybrid Non-dominated Sorting simulated annealing algorithm has been proposed to solve Multiobjective flexible job-shop scheduling problems (MOFJSPs). The multi objectives considered in this study are makespan, total workload of machines, workload of critical machines and total cost simultaneously. In this study, the critical or incapable machines are eliminated by non-dominated sorting of all operations and the initial solution is arrived using simulated annealing. A main feature of this proposed algorithm is its computational efficiency and simplicity in hybridization. The performance of the proposed algorithm is tested with flexible benchmark instances. The experimental results prove its performance by providing non-dominated solutions for both small and relatively larger cases in minimum computational time.

Scheduling problems are generally treated as NP andash; complete combinatorial optimization problems which is a multi-objective and multi constraint one. Repair shop Job sequencing and operator allocation is one such NP andash; complete problem. For such problems, an efficient technique is required that explores a wide range of solution space. This paper deals with Simulated Annealing Technique, a Meta - heuristic to solve the complex Car Sequencing and Operator Allocation problem in a car repair shop. The algorithm is tested with several constraint settings and the solution quality exceeds the results reported in the literature with high convergence speed and accuracy. This algorithm could be considered as quite effective while other heuristic routine fails.

Computer-aided process planning (CAPP) is an important interface between computer-aided design (CAD) and computer-aided manufacturing (CAM) in computer-integrated manufacturing environment. A problem in traditional CAPP system is that the multiple planning tasks are treated in a linear approach. This leads to an overconstrained overall solution space, and the final solution is normally far from optimal or even nonfeasible. A single sequence of operations may not be the best for all the situations in a changing production environment with multiple objectives such as minimizing number of setups, maximizing machine utilization, and minimizing number of tool changes. In general, the problem has combinatorial characteristics and complex precedence relations, which makes the problem more difficult to solve. The main contribution of this work is to develop an intelligent CAPP system for shop-floor use that can be used by an average operator and to produce globally optimized results. In this paper, the feasible sequences of operations are generated based on the precedence cost matrix (PCM) and reward-penalty matrix (REPMAX) using superhybrid genetic algorithms-simulated annealing technique (S-GENSAT), a hybrid metaheuristic. Also, solution space reduction methodology based on PCM and REPMAX upgrades the procedure to superhybridization. In this work, a number of benchmark case studies are considered to demonstrate the feasibility and robustness of the proposed super-hybrid algorithm. This algorithm performs well on all the test problems, exceeding or matching the solution quality of the results reported in the literature. The main contribution of this work focuses on reducing the optimal cost with a lesser computational time along with generation of more alternate optimal feasible sequences. Also, the proposed S-GENSAT integrates solution space reduction, hybridization, trapping out of local minima, robustness, and convergence; it consistently outperformed both a conventional genetic algorithm and a conventional simulated annealing algorithm.