Horizontal Directional Drilling Machine Research Articles

A Designed Calibration Approach for the Measurement-While-Drilling Instrument

The Measurement-While-Drilling (MWD) system, composed of a tri-axial magnetometer and a tri-axial accelerometer, is widely used in the Horizontal Directional Drilling machine in coal mines. This system can provide attitude information of each measuring point in the borehole, which will eventually allow the trajectory of the borehole to be drawn. The attitude information, however, showed a low-level accuracy, due to the sensor’s imperfection and mounting errors. The accuracy worsened when low-cost sensors were employed, as they had higher random noise. Therefore, an exploration of ways to eliminate the sensor imperfection and mounting tolerance as well as to suppress the noise is needed. In this paper, a feasible calibration approach was designed to address these issues. This new approach combined three foundational calibration algorithms, including the ellipsoidal fitting method, the planar fitting method, and the inner product invariance method. The traditional ellipsoidal fitting method and planar fitting method were optimized by using the recursive least square criterion and omitting the steps of sample data acquisition, respectively. In addition, the noise suppression method was involved in our approach to improve the calibration accuracy. The numerical simulation results showed that the number of sampling points decreased significantly, but the accuracy of the azimuthal angle and the pitch angle fully met the engineering requirements. The experimental results showed that the pitch angle error was reduced by less than 0.5°, and the azimuth error was also reduced by less than 2.5°. It should be noted that this new approach could be implemented without the help of other expensive auxiliary equipment.

A decision-making method for complex system design in a heterogeneous language information environment

In the process of designing engineering systems, early system design often plays an important role. Although the existing system design methods are very effective, the preference information of different experts and the uncertainty of their subjective preferences are not processed effectively. Because different stakeholders have different backgrounds and different personalities, their linguistics preferences are expressed differently. Therefore, it is difficult to select a system scheme that meets all the performance requirements and is approved by various stakeholders. To solve this problem, a decision-making method is proposed in this study for complex system design in a heterogeneous language information environment. First, a theoretical system scheme set is constructed through a morphological matrix, and a multi-objective programming model is constructed based on the performance indicators to select the system scheme set that optimises each performance objective and meets the performance constraints. Then, a trapezoidal asymmetric cloud model is used as an intermediary for containing heterogeneous language information to integrate each stakeholder's preference information, as expressed by their favourite linguistic term sets, and to select the best system solution. The effectiveness of the proposed method is verified by a system design example of a horizontal directional drilling machine.

Analysis on the crown convergence deformation of surrounding rock for double-shield TBM tunnel based on advance borehole monitoring and inversion analysis

The surrounding rock deformation during tunnelling is difficult to be measured or calculated accurately, especially in tunnels constructed by double-shield TBM. A method for prediction of the crown convergence deformation of surrounding rock based on advance borehole monitoring and numerical inversion analysis is proposed. Combined with the field deformation monitoring and numerical simulation, the final crown convergence deformation of surrounding rock is obtained. When TBM advances to the test section, the horizontal directional drilling machine is used to drill an advance borehole at the top of tunnel and 1.6 m away from the tunnel face, and the measuring tube with fiber Bragg grating (FBG) sensors has been installed in the borehole to conduct the deformation monitoring. Then, based on the numerical simulation with the viscoplastic creep constitutive model, the final crown deformation of surrounding rock during TBM tunneling process has been predicted, in which the parameters of surrounding rock are obtained through the inversion analysis of deformation data and the error caused by the displacement of reference point has been corrected. The surrounding rock crown convergence deformation was also estimated by using a scaled instrument in the grout hole of lining segment and is approximately the same with the above predicted value, which show that the proposed method can well analyze the surrounding rock crown convergence deformation during tunneling for double-shield TBM tunnels.

A systematic decision-making method for evaluating design alternatives of product service system based on variable precision rough set

Product service systems (PSS) have led global manufacturers to change from providing product only to offering both product and its services as a whole. The existing decision-making methods have difficulties in evaluating design alternatives systematically during PSS conceptual design process involving cognition vagueness and related complex factors. A new systematic decision-making method is developed for judging these alternatives. PSS is divided into multiple-modules associated with function characteristics and then evaluated by using the outputs of parallel houses of quality (HoQs). HoQs can efficiently deal with customer requirements and the relationships between product and service. A variable precision rough set-based approach is proposed to evaluate these alternatives, which can flexibly handle subjectivity and vagueness during the decision-making process. An optimizing model of least squares model is used to integrate individual judgments into a consensus group judgment. A non-deterministic ranking method is developed to identify optimal alternative based on the final judgments which are obtained by using a rough weighted geometric mean method. The proposed method is validated through a real-world case study for a horizontal directional drilling machine.

A systematic decision making approach for product conceptual design based on fuzzy morphological matrix

Conceptual design plays an important role in development of new products and redesign of existing products. Morphological matrix is a popular tool for conceptual design. Although the morphological-matrix based conceptual design approaches are effective for generation of conceptual schemes, quantitative evaluation to each of the function solution principle is seldom considered, thus leading to the difficulty to identify the optimal conceptual design by combining these function solution principles. In addition, the uncertainties due to the subjective evaluations from engineers and customers in early design stage are not considered in these morphological-matrix based conceptual design approaches. To solve these problems, a systematic decision making approach is developed in this research for product conceptual design based on fuzzy morphological matrix to quantitatively evaluate function solution principles using knowledge and preferences of engineers and customers with subjective uncertainties. In this research, the morphological matrix is quantified by associating the properties of function solution principles with the information of customer preferences and product failures. Customer preferences for different function solution principles are obtained from multiple customers using fuzzy pairwise comparison (FPC). The fuzzy customer preference degree of each solution principle is then calculated by fuzzy logarithmic least square method (FLLSM). In addition, the product failure data are used to improve product reliability through fuzzy failure mode effects analysis (FMEA). Unlike the traditional FMEA, the causality relationships among failure modes of solution principles are analyzed to use failure information more effectively through constructing a directed failure causality relationship diagram (DFCRD). A fuzzy multi-objective optimization model is also developed to solve the conceptual design problem. The effectiveness of this new approach is demonstrated using a real-world application for conceptual design of a horizontal directional drilling machine (HDDM).

Risk prioritization in failure mode and effects analysis under uncertainty

Failure mode and effects analysis (FMEA) is a powerful tool for identifying and assessing potential failures. The tool has become increasingly important in new product development, manufacture or engineering applications. Generally, risk assessment in FMEA is carried out by using risk priority numbers (RPNs) which can be determined by evaluating three factors: occurrence (O), severity (S) and detection (D). Due to the vagueness and uncertainty existing in the evaluating process, crisp numbers representing RPNs in the traditional FMEA might be improper or insufficient in contrast to fuzzy numbers. Currently, the fuzzy methods and linear programming method have been proposed as an effective solution for the calculations of fuzzy RPNs. However, considering the fact that fuzzy RPNs are determined on a multidimensional scale spanning O, S and D along with their interactions under a fuzzy environment, several gaps should be bridged in the evaluation, calculation, and ranking of fuzzy RPNs. First, decision makers tend to use multi-granularity linguistic term sets for expressing their assessments because of their different backgrounds and preferences. Second, numerical compensation may be existed among O, S and D that can derive different RPNs in the engineering applications. Third, the complete ranking results for fuzzy RPNs may be easily changed by the effects of uncertain factors. In this study, a fuzzy-RPNs-based method integrating weighted least square method, the method of imprecision and partial ranking method is proposed to generate more accurate fuzzy RPNs and ensure to be robust against the uncertainty. A design example of new horizontal directional drilling machine is used for illustrating the application of the proposed approach.

A new approach for conceptual design of product and maintenance

Services such as maintenance are increasingly important for a manufactured product, which can improve customer satisfaction and promote sustainable consumption. A trend has appeared that manufacturers change their attentions from providing only a product to offering both product and its services as a whole. However, preliminary literature review shows that few studies focus on integrated design of product and service. In the paper, a design approach is proposed for supporting conceptual design of product and maintenance (P&M). In the layout process, the approach uses an improved quality function deployment (QFD) tool to translate customer requirements into concept specifications. An information exchange mechanism is developed to exploit the interrelationships between P&M. In the mechanism, a failure mode and effects analysis (FMEA) tool is used to identify and analyse failure modes and their effects on the product concept. Then maintenance concepts are generated based on the results of QFD and FMEA. The proposed approach is applied in a conceptual design case of a horizontal directional drilling machine with its maintenance. Furthermore, the paper also addresses the management and improvement of P&M concepts.

A new integrated decision-making approach for design alternative selection for supporting complex product development

Design alternative selection is regarded as a crucial activity in complex product development. The traditional decision-making methods barely consider the design alternative evaluation of complex products or integrate the voices of customers into the decision process systematically. The aim of this paper is to improve the effectiveness of decision making about multiple design alternatives in complex product development under uncertainty. Based on the integration of quality function deployment and group decision making, a new decision-making approach is proposed for assisting product designers in selecting the design alternatives of complex products. Meanwhile, fuzzy set theory is incorporated in order to capture the vagueness and uncertainty that exists in the decision process. In this study, a complex product is divided into multi-parts to form a hierarchical structure. Fuzzy quality function deployment is used for translating customer requirements into the priorities of these parts. Furthermore, a fuzzy multi-criteria group decision-making method is employed for evaluating the performance of part alternatives. All design alternatives are ranked and then selected according to the multiplied evaluation scores of parts with their weights. This proposed approach is applied in a real-world example of a horizontal directional drilling machine. In addition, how the importance weights of customer requirements and evaluation criteria change are analysed under various risk environments.

Fuzzy group decision-making for multi-format and multi-granularity linguistic judgments in quality function deployment

As a customer-driven tool, quality function deployment (QFD) is widely used in product planning or improvement to achieve higher product performance and customer satisfaction. QFD uses a matrix called the house of quality (HoQ) to translate customer requirements (CRs) into engineering characteristics (ECs). Constructing the HoQ, which includes determining the importance weights of CRs, the correlation matrix among ECs and the relationship matrix between CRs and ECs, is an important issue in the application of QFD. However, decision-makers (DMs) participating the construction of HoQ tend to give their individual judgments in multi-format or multi-granularity depending on their different knowledge, experience, culture and circumstance. Furthermore, these judgments are more difficult to assess with the precise quantitative forms due to the vagueness and uncertainty existed in the early stage of new product development. In this paper, a group decision-making approach incorporating with two optimization models (i.e. logarithmic least squares model and weighted least squares model) is proposed to aggregate these multi-format and multi-granularity linguistic judgments. Fuzzy set theory is utilized to address the uncertainty in the decision-making process. The proposed method is illustrated with a real-world case of horizontal directional drilling machine. The application indicates that the group decision-making method may be a promising tool for constructing the HoQ.