In this article, a method of hybrid convolutional neural networks (CNNs) is proposed for powder-bed fusion (PBF) process monitoring. The proposed method can learn both the spatial and temporal representative features from the raw images automatically based on the advantages of the CNN architecture. The results demonstrate the superior performance of the proposed method compared with the traditional methods with handcrafted features. The overall detection accuracy of four process conditions, e.g., overheating, normal, irregularity, and balling, can be up to 0.997. In addition, it is found that the temporal information for PBF process monitoring by the vision detection of the process zone (including melt pool, plume, and spatters) is significant. As the proposed method can save image processing steps, it simplifies the procedure on feature extraction. This makes it more suitable for online monitoring applications.

The nine papers in this special section focus on Big Data analytics in intelligent manufacturing systems. These systems can automatically adapt to changing environments and varying process requirements with minimal supervision and assistance from operators. It is essentially a cyber–physical production system that has enhanced intelligence due to learning, reasoning, adaptation, and decision making. The success of intelligent manufacturing relies on the timely acquisition, distribution, and utilization of various types of data from machines, manufacturing process, and products. The efficient use of big data can enhance the intelligence and automation of manufacturing process, provide high quality products and just-in-time production, and increase productivity and reduce costs. For example, by analyzing the factory floor data, equipment monitored data, and the enterprise manufacturing database, it could help to store, explore, and make complex decisions for the manufacturing system. While these big data topics have been widely discussed in the public media and the theory has been rigorously treated by statisticians and computer scientists from academia, little has been explored in the manufacturing research community from an engineering point of view. This special section aims to bridge the gap, and provides a platform for the communities to report recent findings and emerging research developments in the field.

Soft robots, primarily made out of intrinsically soft materials, have flourished greatly in the past decade due to their advantages such as flexibility and adaptability over rigid-bodied robots. A rich repertoire of soft robots designed from intuitive or biomimetic approaches have been developed to provide new solutions for robots. However, these design approaches are limited by the designers' experience and inspiration, and a systematic design methodology for soft robots is still missing. We tackle this issue by mathematically recasting the design problem under the framework of topology optimization problem. To demonstrate the effectiveness of the proposed methodology, in this paper, we develop a pneumatically actuated soft gripper consisting of three fingers, each finger is able to undergo a free travel bending and deliver a grasping force. Hence, each gripper finger is designed as a continuum compliant mechanism to achieve its maximal bending deformation. The proposed soft gripper with complex shape is directly fabricated through 3D printing technology. Experimental results show that the deflected soft finger is able to achieve a 41° free travel bending and generate 0.68N blocked force upon 0.11MPa actuation pressure. This work represents an important step towards the goal of designing soft robots automatically.

This paper investigates the UAV mission planning problem in which one needs to find the optimal plan/schedule to carry out various tasks of different time windows at various locations using a fleet of fixed-winged heterogeneous UAVs. For this realistic and complex UAV mission planning problem, a two-step approach is proposed to solve it: flying path planning and task scheduling. The solution method includes a graph-based search algorithm to solve path planning problem and a MILP-based algorithm to solve task scheduling problem. To test the effectiveness and efficiency of the developed algorithms, experiments were designed and carried out. It shows that the developed algorithms can solve the defined UAV mission planning problem effectively.

A good concurrency control method that maximizes the operational parallelism while prevents conflicts of simultaneous manipulations is vital for cooperative design systems and still a challenge. We propose an adaptive granular concurrency control approach for the replicated collaborative feature modeling based on the feature dependency directed acyclic graph (FDAG). According to the varying design contexts, an adaptive granularity for concurrent manipulations is determined dynamically by the FDAG of the replicated model to avoid concurrent regeneration conflicts. A prototype is realized on a real-time collaborative design system consisting of heterogeneous CAD systems. The preliminary results show that the approach proposed is promising.

Concurrency control with a reasonable granularity is one of open challenges in cooperative design systems. In this paper, a fine granular concurrency control mechanism is proposed to support simultaneous feature modifications during cooperative design activities. First, extend a de-centralized mutual exclusion agreement on a single critical section to a fully distributed concurrency control mechanism supporting multiple critical sections. Second, a feature-level concurrency control framework is devised for peer-to-peer cooperative design environments to ensure the consistency of replicated models after concurrent manipulations. Finally, a prototype of the proposed mechanism is realized on a real-time cooperative design environment consisting of two heterogeneous CAD systems, SolidWorks and Autodesk Mechanical Desktop.

This paper discusses the effect of geometric shape on the accuracy of direct metal laser sintering (DMLS) prototypes. The percentage shrinkages due to different shapes are investigated and their empirical relationship is determined. A new speed-compensation (SC) method is proposed to reduce uneven shrinkage affected by the two-dimensional geometric shape at each layer. From case studies conducted, the optimized SC method is found to be efficient in improving the accuracy of prototypes fabricated. Note to Practitioners-This paper aims to address the problem of dimensional errors of parts built by the direct metal laser sintering (DMLS) process. Existing compensation approaches are normally based on a general relationship between the nominal dimensions and the errors after sintering. However, the effect arising from different geometric shapes is not considered. A new approach is proposed using different scan speed settings to compensate for the effect of geometric shapes to improve the dimensional accuracy of the entire part. During processing, the laser sinters along the trajectory are guided by the hatch vectors or dexel. An appropriate experimental method is used to establish the relationship for different scan speeds with the dexel length to the final accuracy. When building the part, the laser scan speed is adjusted dynamically according to the dexel length which varies with the geometric shape of the part. The case study demonstrates that the proposed method can generate correct speed settings to effectively increase the dimensional accuracy of the final part. Although this method has been developed based on the DMLS process, it is also applicable to other laser sintering processes. In future research, other process parameters, such as laser power, will be considered independently, or together with the scan speed, for possible further improvement on the dimensional accuracy.

The factors that generally affect the slicing error in layered manufacturing (LM) processes are first analyzed, and issues pertaining to the current methods to deal with the slicing error are discussed in this paper. A method based on a recently developed and implemented orthogonal LM system to reduce the overall slicing error is presented. In this method, the flat region is separated from the stereolithography (STL) model and different processing methods are applied to the different areas in the part geometry. In addition, the mathematical model for calculating the slicing error is derived and an approach based on a genetic algorithm has been developed to optimize the build orientation in terms of minimizing the slicing error. Case studies are given to demonstrate the effectiveness and efficiency of the method. Note to Practitioner-The staircase effect has been the major concern for industry to widely adopt rapid prototyping technologies. It will not only worsen the surface quality but also create errors on the parts built. This paper introduces a novel approach to minimizing staircase errors based on a multidirectional deposition approach. A mathematical method combined with a generic algorithm is used to minimize the slicing errors. From the case study given, the approach has been proven to be effective in minimizing staircase errors and thus improving the rapid prototyping (RP) built part quality.

Fixture design is an important manufacturing activity which affects the quality of parts produced. In order to develop a viable computer-aided fixturing tool, the fixture-workpiece system has to be accurately modeled and analyzed. This paper describes the modeling, analysis, and verification of optimal fixturing configurations by the methods of force closure, optimization, and finite-element modeling (FEM). Force closure has been employed to find optimal clamping positions and sequencing, while optimization is used for determining the minimum clamping forces required to balance the cutting forces. The developed FEM is able to determine in detail what are the reaction forces, workpiece displacement, deformation in the workpiece and fixtures. In order to produce a more accurate model for predicting the behavior of the fixture-workpiece system, the developed FEM includes fixture stiffness, which past models have assumed as rigid bodies. The reaction forces on the locators are experimentally verified. A sensor-embedded experimental fixturing setup was developed to verify the modeling and the data was used to compare with the FEM. Note to Practitioners-In practice, the machinist applies excessive force to hold the part on machine table, so that it does not move when machining is carried out. However, while machining flexible parts or clamping on finished surfaces, care must be taken so that only necessary and optimal clamping forces are applied, to avoid deforming the part or damaging the surface. Therefore, in this study, we have developed a mathematical model to characterize the mechanics and conditions for a fixture to hold a given part. The developed mathematical model computes the optimal clamping forces required to hold the part in position, given the cutting conditions. The result obtained was verified by conducting the machining test using the developed sensor-embedded experimental fixture setup. The FEM was also developed to predict the behavior of fixture-workpiece system and the results obtained were encouraging.

Path generation is an important factor that affects the quality and efficiency of most layered manufacturing processes such as SLS, SLA and FDM. This paper introduces an efficient path generation algorithm. The principle of the algorithm and the implementation are presented. A comparative study is used to analyze the effectiveness of this method. The results of comparison on both the path length and processing time between the traditional method and the proposed method are discussed.

This paper presents an off-line simulation approach that aims to provide a model-based online control of a proposed intelligent fixturing system. The intelligent fixturing system is to adaptively adjust the clamping forces to optimal values during the machining process. Using the off-line simulation, an analytical fixture-workpiece model and an optimization method have been developed for the control of a fixturing system. This simulation can also be applied to evaluate the performance of a fixturing system and determine optimal clamping forces for a given fixture configuration. Experiments have been conducted to verify the proposed model. The fixturing system can be applied in a high-precision machining environment where the workpiece deformation due to over-clamping and improper machining is a major concern.