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The purpose of this paper is to survey and express the advantages and disadvantages of the existing approaches for solving grey linear programming in decision-making problems.

After presenting the concepts of grey systems and grey numbers, this paper surveys existing approaches for solving grey linear programming problems and applications. Also, methods and approaches for solving grey linear programming are classified, and its advantages and disadvantages are expressed.

The progress of grey programming has been expressed from past to present. The main methods for solving the grey linear programming problem can be categorized as Best-Worst model, Confidence degree, Whitening parameters, Prediction model, Positioned solution, Genetic algorithm, Covered solution, Multi-objective, Simplex and dual theory methods. This survey investigates the developments of various solving grey programming methods and its applications.

Different methods for solving grey linear programming problems are presented, where each of them has disadvantages and advantages in providing results of grey linear programming problems. This study attempted to review papers published during 35 years (1985–2020) about grey linear programming solving and applications. The review also helps clarify the important advantages, disadvantages and distinctions between different approaches and algorithms such as weakness of solving linear programming with grey numbers in constraints, inappropriate results with the lower bound is greater than upper bound, out of feasible region solutions and so on.

The study discusses existing scenario methods in business and technology foresight and introduces electronically mediated scenario process in two varieties. The purpose of the study is to discuss the existing practice, position the IDEAS and SAGES methods, and outline their contribution to the state of the art.

The paper takes the form of a literature study and conceptual discussion, illustrated with a case example of electronically mediated scenario methods.

Both of the presented scenario methods, i.e. IDEAS and SAGES, are feasible means to compose scenarios. The methods can be positioned respectively to intuitive‐logical and heuristic schools of thought. The contribution to existing practice is that they consume fewer resources than do their more traditional counterparts.

The empirical validation of the presented methods is presently limited to case studies. Thus, the authors invite practitioners and researchers to examine the methods and to discuss the applicability of the results.

The IDEAS and SAGES methods offer tools for practicing managers to conduct scenario planning with practitioners and experts in a flexible and effective manner.

The paper adds to the ongoing discussion on business and technology foresight by presenting the novel scenario methods, and positioning them explicitly to the existing practice.

The purpose of this paper is to propose a new method based on three-dimensional (3D) vision technologies and human skill integrated deep learning to solve assembly positioning task such as peg-in-hole.

Hybrid camera configuration was used to provide the global and local views. Eye-in-hand mode guided the peg to be in contact with the hole plate using 3D vision in global view. When the peg was in contact with the workpiece surface, eye-to-hand mode provided the local view to accomplish peg-hole positioning based on trained CNN.

The results of assembly positioning experiments proved that the proposed method successfully distinguished the target hole from the other same size holes according to the CNN. The robot planned the motion according to the depth images and human skill guide line. The final positioning precision was good enough for the robot to carry out force controlled assembly.

The developed framework can have an important impact on robotic assembly positioning process, which combine with the existing force-guidance assembly technology as to build a whole set of autonomous assembly technology.

This paper proposed a new approach to the robotic assembly positioning based on 3D visual technologies and human skill integrated deep learning. Dual cameras swapping mode was used to provide visual feedback for the entire assembly motion planning process. The proposed workpiece positioning method provided an effective disturbance rejection, autonomous motion planning and increased overall performance with depth images feedback. The proposed peg-hole positioning method with human skill integrated provided the capability of target perceptual aliasing avoiding and successive motion decision for the robotic assembly manipulation.

The purpose of this study is to present a new and relatively inexpensive method for posture evaluation of the positioning of the wing-body assembly. Positioning is an essential process to guarantee alignment accuracy in an assembly line.

The studied method includes a structural set-up and a software algorithm used to process a set of experimental input data to compute the actual position of the wing with respect to the ideal position, which is proposed considering measurement uncertainty, the deviation caused by large errors in measurement points and the different tolerance requirements.

The studied method has been found to be simple and effective in addition to being highly accurate. Compared with most of the current methods that have been developed with optical equipment, it is more cost- and space-efficient. The automation process determines how much operation time will be saved.

The studied method has been applied in an actual assembly line, and the economic and time savings illustrate its benefits.

This method provides an attractive wing-body assembly solution for those enterprises that want to find a low-cost option or have limited measuring space for optical equipment. It can also be the basis for the accurate assembly of other large parts for aircraft and other vessels.

THIS article is intended as a continuation of the previous one on hull construction. The blue‐print drawings, as before, have to be developed full‐scale on the scrive board, which must be large enough to carry all the lines without any overlapping.

The positioning and grasping of large-size objects have always had problems of low positioning accuracy, slow grasping speed and high application cost compared with ordinary small parts tasks. This paper aims to propose and implement a binocular vision-guided grasping system for large-size object with industrial robot.

To guide the industrial robot to grasp the object with high position and pose accuracy, this study measures the pose of the object by extracting and reconstructing three non-collinear feature points on it. To improve the precision and the robustness of the pose measuring, a coarse-to-fine positioning strategy is proposed. First, a coarse but stable feature is chosen to locate the object in the image and provide initial regions for the fine features. Second, three circular holes are chosen to be the fine features whose centers are extracted with a robust ellipse fitting strategy and thus determine the precise pose and position of the object.

Experimental results show that the proposed system has achieved high robustness and high positioning accuracy of −1 mm and pose accuracy of −0.5 degree.

It is a high accuracy method that can be used for industrial robot vision-guided and grasp location.

The purpose of this paper is to develop a new method of evaluating the present state of X‐ray machines used in the electronics device manufacturing industry.

There are several kinds of failures that can only be detected by means of X‐ray inspection. The capabilities and properties of such machines, however, alter over a period of time. The effects of these changes are rarely published and when they are, the significance and reliability of the results produced depends very much on the state and capabilities of the machines in question.

The effectiveness and appropriateness of the present methods of calibration have been investigated. The optimization of the prevalence and effectiveness of these calibrations is described. Suggestions are also made as to the necessary adjustments or repairs that are required to reach the ideal optimized state of X‐ray machines. A scientifically substantiated method is also presented that can be efficiently employed in practise during automated X‐ray inspections of electronic devices.

In this paper, a new method of testing automated X‐ray inspection systems is introduced. It is clear that the method currently used by many engineers and inspection system manufacturers is not in itself sufficient, as they do not test grey‐scale and positioning stability in relation to changes that occur over time. Further, there is no evidence that numerical testing of the image quality takes place. Detailed investigations have been carried out to find the best methods to measure these parameters.

As a result of the advancement of the online environment, several methodological proposals emerged to establish procedures for digital qualitative research. While the various online ethnography methods overlap, they are not equivalent in terms of their theoretical bases, procedures and goals. The purpose of this article is to add clarity to their main differences, depicting specificities, potentialities and limitations of each method.

This conceptual article results from an integrative literature review that brought together studies that proposed, debated or used qualitative research methods in the digital environment. The research focused on the primary indexed journals publishing cultural studies in the past 20 years.

The literature review highlights four methods – virtual ethnography, digital ethnography, netnography and the post-application programming interface ethnography. The integrative literature review adds clarity depicting the main premises and procedures of each method. The present analysis positions the different methods considering two dimensions: the focus on the boundaries of the group/culture investigated, and the focus on the platform agency, affordances and specific dynamics.

The article proposes a comparative framework outlining points of convergence and divergence to create a reference for researchers on topics of significance while designing and conducting a research study in a digital environment. This conceptual organization highlights and supports qualitative researchers on their methodological challenges.

Flexible tooling for adjusting the posture of large components of aircraft (LCA) is composed of several numerical control locators (NCLs). Because of the manufacture and installation errors of NCL, the traditional control method of NCL may cause great interaction force between NCLs and form the internal force of LCA during the process of posture adjustment. Aiming at this problem, the purpose of this paper is to propose a control method for posture adjustment system based on hybrid force-position control (HFPC) to reduce the internal force of posture adjustment.

First of all, the causes of internal force of posture adjustment were analyzed by using homogeneous transformation matrix and inverse kinematics. Then, axles of NCLs were divided into position control axle and force control axle based on the screw theory, and the dynamic characteristics of each axle were simulated by MATLAB. Finally, a simulated posture adjustment system was built in the laboratory to carry out HFPC experiment and was compared with the other two traditional control methods for posture adjustment.

The experiment results show that HFPC method for redundant actuated parallel mechanism (RAPM) can significantly reduce the interaction force between NCLs.

In this paper, HFPC is applied to the control of the posture adjustment system, which reduces the internal force of LCA and improves the assembly quality of aircraft parts.