Assembly Operations Research Articles

People, performance and transition: A case study of psychological contract and stakeholder orientation in the Toyota Australia plant closure

AbstractOperations managers often manage in times of change that exert pressure on values and methods usually developed during more stable eras. With increasing global volatility, companies open and close plants because of demand shifts, cost and reshoring considerations, and government‐induced and market forces. Impacts of plant closures on local communities, employees, suppliers, and other stakeholders have been documented, but plant closure processes have not been extensively studied. This paper describes an engaged research study of Toyota Australia's manufacturing closure processes. We apply psychological contract theory, particularly of contract breach, to examine the “respectful” approach Toyota used to close its assembly operation in Melbourne. We examined the role that stakeholder theory plays in describing managerial motivations. Toyota allocated resources beyond typical expectations to prepare its workforce for their post‐Toyota careers and lives. During the 4‐year transition process, employee performance, and engagement improved, supporting propositions that reserves of employee goodwill can come into play when a psychological contract breach occurs. Further, leadership actions can moderate the negative impacts predicted by that theory, beyond outcomes that more transactional views would predict. Our study offers an elaborated model of psychological contract breach that future researchers can apply to plant closures and related operational contexts.

Kinematic screws and dual quaternion based motion controllers

This paper presents a motion control approach with a focus on robotic manipulators based on screw theory and dual quaternions. The stability analysis of a general dual quaternion based controller has been capitalized to design an additional bounded twist controller. This controller is proposed to limit the maximum twist of the end-effector within a desired value, while preserving the accuracy achievable with high-gain feedback controllers. The proposed controllers could be useful for robotic tasks where curved motion is preferred over straight line motion. In that regard, the trajectories taken by the proposed controllers were analyzed for pose-to-pose control and some strategies have been provided for the proposed coupled controller to modify the natural trajectory. These behaviors were verified on a real robot as well as in simulation, comparing the experimental results with conventional decoupled controllers. The proposed controllers achieved smooth coupled motions which can be useful for tasks such as pick and place and assembly operations. Moreover, our coupled controllers based on screw theory need less actuator motion than the conventional decoupled approach for certain situations.

Completion and Installation of the ITER Lower Poloidal Field Coils PF5 & 6

The poloidal magnetic field of ITER is provided by 6 Niobium–Titanium (NbTi) coils mainly for plasma shaping and position control. The fabrication of the two lower coils PF6 from China ASIPP and PF5 from European F4E has been completed and the coils installed in the bottom of the Tokamak pit in 2021. This paper presents the challenge of the manufacturing process, which involves manufacturing of several dozens of superconducting double pancakes, requiring bending, insulating and welding steps to keep accuracy of a few mm on dimensions up to 25m. The reproducibility and reliability of the manufacturing processes to manage magnet winding/insulation and cryogenic skills are essential for final quality and schedule robustness. After having successfully completed final thermal cycles for site acceptance in Cadarache, the PF6 and PF5 have been delivered simultaneously and handed over to IO. This paper demonstrates the assembly scenario of the two coils, including assembly tools for transportation, preparation for lifting, lifting tooling design, temporary supports design in cryostat and alignment of positioning on supports from assembly hall to the tokamak pit. The coils are sensitive components and preservation steps are needed to protect them in the pit during other assembly operations. In future, the two coils will sit in pit for several years until mounted onto the TF coils through the support then connected to feeders at the coil terminals. PF6, PF5 will firstly rest on temporary supports, and later shift up by jacks and conical guides to align onto TFC. The alignment & shimming processes and tightening will be presented to show the practical functionality and avoidance of interferences with the other components of the ITER tokamak which achieving high accuracy to avoid error fields.

Hydrophobicity Graded Gas Diffusion Layer for Stable Electrochemical Reduction of CO2

AbstractTo mitigate flooding associated with the gas diffusion layer (GDL) during electroreduction of CO2, we report a hydrophobicity‐graded hydrophobic GDL (HGGDL). Coating uniformly dispersed polytetrafluoroethylene (PTFE) binders on the carbon fiber skeleton of a hydrophilic GDL uniformizes the hydrophobicity of the GDL and also alleviates the gas blockage of pore channels. Further adherence of the PTFE macroporous layer (PMPL) to one side of the hydrophobic carbon fiber skeleton was aided by sintering. The introduced PMPL shows an appropriate pore size and enhanced hydrophobicity. As a result, the HGGDL offers spatial control of the hydrophobicity and hence water and gas transport over the GDL. Using a nickel‐single‐atom catalyst, the resulting HGGDL electrode provided a CO faradaic efficiency of over 83 % at a constant current density of 75 mA cm−2 for 103 h operation in a membrane electrode assembly, which is more than 16 times that achieved with a commercial GDL.

Hydrophobicity Graded Gas Diffusion Layer for Stable Electrochemical Reduction of CO2.

To mitigate flooding associated with the gas diffusion layer (GDL) during electroreduction of CO2 , we report a hydrophobicity-graded hydrophobic GDL (HGGDL). Coating uniformly dispersed polytetrafluoroethylene (PTFE) binders on the carbon fiber skeleton of a hydrophilic GDL uniformizes the hydrophobicity of the GDL and also alleviates the gas blockage of pore channels. Further adherence of the PTFE macroporous layer (PMPL) to one side of the hydrophobic carbon fiber skeleton was aided by sintering. The introduced PMPL shows an appropriate pore size and enhanced hydrophobicity. As a result, the HGGDL offers spatial control of the hydrophobicity and hence water and gas transport over the GDL. Using a nickel-single-atom catalyst, the resulting HGGDL electrode provided a CO faradaic efficiency of over 83 % at a constant current density of 75 mA cm-2 for 103 h operation in a membrane electrode assembly, which is more than 16 times that achieved with a commercial GDL.

MEMS Tunable Metasurfaces Based on Gap Plasmon or Fabry–Pérot Resonances

Tunable metasurfaces promise to enable adaptive optical systems with complex functionalities. Among possible realizations, a recent platform combining microelectromechanical systems (MEMS) with gap-surface plasmon (GSP) metasurfaces offers high modulation efficiency, broadband operation, and fast response. We compare tunable metasurfaces operating in GSP and Fabry–Pérot (FP) regions by investigating polarization-independent blazed gratings both numerically and experimentally. Peak efficiency is calculated to be ∼75% in both cases (∼40% in measurements), while the operation bandwidth is found larger when operating in the GSP region. Advantages of operating in the FP region include relaxed assembly requirements and operation tolerances. Additionally, simulation and experimental results show that coupling between neighboring unit cells increases for larger air gaps, resulting in deteriorated efficiency. We believe the presented analysis provides important guidelines for designing tunable metasurfaces for diverse applications in miniaturized adaptive optical systems.

Optimalisasi Waktu Kerja Karyawan Menggunakan Metode Hungarian (Studi Kasus CV Bintang Jaya)

<p><em>The most common problem in business and industry today is the optimal allocation of production resources, i.e. providing different levels of productivity in different tasks. The challenge of CV Bintang Jaya is how to optimize working hours according to the working hours of its employees. The purpose of this study is to determine the working time of employees in accordance with the work. The research method used is hungarian using the POM-QM application for Windows. Data are collected through observation, interviews, documentation and literature study. From this study, the best results are obtained based on the work. Employee 1 takes 17 minutes to perform the wood cutting operation, employee 2 takes 35 minutes to make a pattern, employee 3 takes 10 minutes to perform the smoothing operation, and employee 4 takes 10 minutes to perform the assembly operation.</em><em></em></p>

Toward Proactive Human–Robot Collaborative Assembly: A Multimodal Transfer-Learning-Enabled Action Prediction Approach

Human–robot collaborative assembly (HRCA) is vital for achieving high-level flexible automation for mass personalization in today’s smart factories. However, existing works in both industry and academia mainly focus on the adaptive robot planning, while seldom consider human operator’s intentions in advance. Hence, it hinders the HRCA transition toward a proactive manner. To overcome the bottleneck, this article proposes a multimodal transfer-learning-enabled action prediction approach, serving as the prerequisite to ensure the proactive HRCA. First, a multimodal intelligence-based action recognition approach is proposed to predict ongoing human actions by leveraging the visual stream and skeleton stream with short-time input frames. Second, a transfer-learning-enabled model is adapted to transfer learnt knowledge from daily activities to industrial assembly operations rapidly for online operator intention analysis. Third, a dynamic decision-making mechanism, including robotic decision and motion control, is described to allow mobile robots to assist operators in a proactive manner. Finally, an aircraft bracket assembly task is demonstrated in the laboratory environment, and the comparative study result shows that the proposed approach outperforms other state-of-the-art ones for efficient action prediction.

The multi-manned joint assembly line balancing and feeding problem

The Joint Assembly Line Balancing and Feeding Problem (JALBFP) assigns a line feeding mode to each component (Assembly Line Feeding Problem) and each task to a workplace of a station (Assembly Line Balancing Problem). Current literature offers numerous optimisation models that solve these problems sequentially. However, only few optimisation models, provide a joint solution. To solve the JALBFP for a multi-manned assembly line, we propose a Mixed Integer Linear Programming (MILP) model and a heuristic that relies on the Adaptive Large Neighborhood Search (ALNS) framework by considering multiple workplaces per station and three different feeding policies: line stocking, travelling kitting and sequencing. The objective function minimises the cost of the whole assembly system which considers supermarket, transportation, assembly operations, and investment costs. Although the JALBFP requires higher computation times, it leads to a higher total cost reduction compared to the sequential approach. Through a numerical study, we validate the heuristic approach and find that the average deviation to the MILP model is around 1%. We also compare the solution of the JALBFP with that of the sequential approach and find an average total cost reduction of 10.1% and a maximum total cost reduction of 43.8%.

Development of a prediction model for the probability of failure-free operation of elements and components of the main equipment of hydroelectric power plant

A structural diagram of calculation of reliability of hydraulic turbines is proposed taking into account control of arameters of state of system elements, based on data of the map of setpoints of automation and process protection of hydroturbine of HPP. Failure-free operation of hydraulic unit systems and assemblies was analyzed for reliability indicators. The main elements of the system are identified. The safety of HPP operation largely depends on the reliability of the main generating equipment. Hydroturbine equipment of a hydroelectric power plant is designed for specific operating conditions characteristic for each type of hydroelectric power plant. This allows for each type of turbine to efficiently obtain the greatest amount of hydraulic power if they operate under proper conditions. Therefore, when evaluating reliability indicators, it is proposed to take into account weighting factors reflecting the degree of influence of a particular parameter on the reliability of the system. The obtained results were compared according to the proposed model and according to the regulatory methodology for assessing the probability of system failure-free operation in a generalized form. Based on the results, a model is proposed that takes into account the failures of the hydraulic unit elements to predict the probability of trouble-free operation in order to ensure the reliability of equipment operation beyond the design service life and reduce operating costs.

Structure-improved current collector for performance enhancement of electrolyte membrane dehumidifiers: 3D simulations and in-situ measurements

Electro-dehumidification based on proton exchange membrane (PEM) is promising owing to its compact assembly and convenient operation. By numerically improving the effects of current collectors’ structure on the operation performance (moisture removal rate, current/temperature/humidity distribution and energy utilization rate), this research achieved a significant dehumidification enhancement (more than 40%) for electrolyte membrane dehumidifiers. 3D Multiphysics simulation and in-situ verification measurements were conducted. Compared with the original collectors, the dehumidification rate can be enhanced by 35% with the “口” collectors, and by more than 40% with “X”, “#” and “▪” collectors. The best performance occurred with the anode collector of “▪” structure (opening area: 9 × 10-4 m2), which the rate increased by 46%. The improvement effects were mainly due to the improvement of potential distribution (especially on the anode side) and the concentration of the reactant (water vapor) reaching the catalyst interface. Compared with the “口” type, the current density uniformity of membrane dehumidifier with the “▪” collector increased from 0.0033 to 0.032. The temperature and moisture distribution were also more uniform. The opening structure of anode collector resulted in a more significant effect than the opening area. Therefore, the system energy utilization rate and COP (coefficient of performance) can be doubled, up to 3.48 × 10−2 g·J−1·m−2 and 0.26, respectively. This research provides a theoretical basis and practical direction for improving current collectors of PEM dehumidifiers.

Ultrasonic and phased-array inspection in titanium-based alloys: A review

Ultrasonic testing procedures are among the most extensively used techniques in non-destructive testing and non-destructive evaluation systems. Meanwhile, phased array inspection or phased-array ultrasonic testing techniques as a well-known type of ultrasonic testing in advanced non-destructive testing systems are utilized in numerous applications, including oil and gas, medical imaging applications, railway, automotive, marine, and aviation industries. Phased-array ultrasonic testing-based methods can also be used in a variety of weld inspections, bond testing, thickness profiling, flaw detections, corrosion inspections, and in-service crack detection. The rapidity, safety, easiness, affordable price, and accurate visualization of phased array in measuring the defect characteristics such as size, shape, depth, and orientation allow its wide usage and even as a substitute for other inspection methods like radiographic methods. In phased array methods, more than one sound wave is employed to enhance the reliability and flexibility of inspection through the operation of several transducer assemblies, involving 16 to 256 small individual elements. Titanium having many desirable properties like high strength to weight ratio found many industrial applications, which highly necessitates its persistent inspection. For this aim, the present study focuses on the application of the phased-array ultrasonic testing technique for inspecting Ti components specifically in additive manufacturing, welding inspections, and defect detection of complex geometries and composites. Moreover, modern applications and improved computation methods are discussed. The development of phased-array ultrasonic testing inspection systems, particularly high throughput and efficient in situ and mobile equipment, and new computation methods will open new horizons toward the highly sophisticated inspection procedures.

Delamination of Fibre Metal Laminates Due to Drilling: Experimental Study and Fracture Mechanics-Based Modelling

Fibre metal laminates (FML) are significantly adopted in the aviation industry due to their convenient combination of specific strength, impact resistance and ductility. Drilling of such materials is a regular pre-requisite which enables assembly operations, typically through rivet joining. However, the hole-making operation is of increased complexity due to the dissimilarity of the involved materials, often resulting in defects (i.e., material interface delamination), which can significantly compromise the otherwise excellent fatigue strength. This work explores the potential of three different drill geometries, operating under variable cutting speeds and feeds on CFRP-AA laminates. In addition, the usage of sacrificial back support is investigated and cutting load, surface roughness and delamination extension are examined. In order to predict delamination occurrence, ADCB tests are performed, enabling the calculation of fracture energy threshold. Drill geometry presents a very significant influence on delamination occurrence. The usage of specific step-tools with secondary cutting edge showed superior performance. Despite its simplicity, the applied critical force threshold model was able to successfully predict interface delamination with good accuracy.

LARGE SIZED PRODUCT SHELLS DISPLACEMENT MEASUREMENT UNDER STATIC LOADING USING LASER TRACKERS

In the aerospace industry the accuracy of product geometry and the aerodynamic contour provided traditionally, by the mould loft template method. The assembly accuracy control is carried out using optical measuring instruments, such as a level and a theodolit in combination with leveling rulers came to the aircraft industry from geodesy. Measurements are carried out according to reference points pre-embedded in the product at the design stage.
 The introduction of modern high precision coordinate measuring machines (CMM) into the production cycle is promising and actively developing direction to improve the quality of manufactured aircraft. To control the geometry of parts and assemblies, stationary portal-type CMMs and mobile CMMs of the "hand" type replace traditional rod tools and templates, and in the assembly and control operations of the product, traditional optical devices are replaced by a laser tracker. 
 The aim of this paper is the use of laser trackers for non-contact real-time large-sized product shell displacement measurement under static loading, which makes it possible to reduce the complexity and duration of tests, and ensure high measurement accuracy.

A Novel Efficient Convolutional Neural Algorithm for Multi-Category Aliasing Hardware Recognition.

When performing robotic automatic sorting and assembly operations of multi-category hardware, there are some problems with the existing convolutional neural network visual recognition algorithms, such as large computing power consumption, low recognition efficiency, and a high rate of missed detection and false detection. A novel efficient convolutional neural algorithm for multi-category aliasing hardware recognition is proposed in this paper. On the basis of SSD, the novel algorithm uses Resnet-50 instead of VGG16 as the backbone feature extraction network, and it integrates ECA-Net and Improved Spatial Attention Block (ISAB): two attention mechanisms to improve the ability of learning and extract target features. Then, we pass the weighted features to extra feature layers to build an improved SSD algorithm. At last, in order to compare the performance difference between the novel algorithm and the existing algorithms, three kinds of hardware with different sizes are chosen to constitute an aliasing scene that can simulate an industrial site, and some comparative experiments have been completed finally. The experimental results show that the novel algorithm has an mAP of 98.20% and FPS of 78, which are better than Faster R-CNN, YOLOv4, YOLOXs, EfficientDet-D1, and original SSD in terms of comprehensive performance. The novel algorithm proposed in this paper can improve the efficiency of robotic sorting and assembly of multi-category hardware.

Data-Based Assembly Patterns for Overall Equipment Effectiveness at Semi-Automatic Assembly Lines

In industrial practice, production planning is a key factor for manufacturers and suppliers. The entire planning process spans from the appearance of the customer demand to the fulfillment of the demand. Operational execution is based on pre-planned production processes and operations using properly allocated resources. The accurate planning of assembly operations within production is an extremely complex process in terms of efficiency. Predicting stochastically variable efficiencies is difficult due to the ever-changing manufacturing conditions. This paper defines typical assembly process situations for a semi-automatic assembly line and examines their consequence for the Overall Equipment Effectiveness (OEE). Firstly, a literature review demonstrates the scientific relevance. Secondly, the classification of patterns based on assembly process description parameters is described taking into account the positive and negative effects on the OEE. In addition, the assembly patterns and their characteristics are illustrated through a real automotive example.

Methodology to eliminate errors in machining processes through Augmented Reality Applications

Today, precision machining companies must implement new technologies to meet the requirements of the aerospace and automotive industries to maintain their competitiveness in the market and create new business opportunities. It has currently been observed that machining companies face errors in their processes that affect the quality of the products, the operation of the process, the useful life of the machines, and the tools. This research project aims to develop a methodology to reduce errors in Computerized Numerical Control machining (CNC) processes with Augmented Reality Applications (AR-Apps) that help operators interpret manufacturing drawings and assembly operations optimize Setup operations and ensure the reliability of the machining. It begins with a questionnaire applied to a sample of machining companies from Chihuahua Mexico City. To identify the factors that generate critical errors in the machining processes. The main results obtained in this paper are reduction of downtime, elimination of scrap, increment cutting tools life, optimize the machining process, increase productivity, and improved product quality. AR -apps implementation offers a low-cost alternative solution that operators and technicians can use very easily because it is a powerful tool that helps work more efficiently through virtual environments, reducing errors and optimizing the process of machining.

An experimental investigation on the influence of different surface curvatures in drilling machinability of carbon fiber reinforced plastic

Composites used in many fields today are produced by different methods and have different surface curvatures and geometries. Thus, these materials can exhibit different behaviors in terms of machinability characteristics as well as mechanical tests. Drilling operation is an inevitable process for assembly operations of many parts, and in some cases, concave/convex composite parts must also be drilled. In this study, drilling machinability of flat, convex, and concave curved carbon fiber reinforced plastics were investigated experimentally. The machinability was evaluated considering thrust force, delamination formation, and borehole damage analysis. The experimental results demonstrate that the largest thrust force and damage occurs when drilling the flat surface, while the least ones occur when drilling the concave curved surface, in general. In addition, while the damage caused by drilling is severe on the flat surface, higher quality holes were obtained on the concave curved surface at the same cutting parameters.

The effects of supply variability on the performance of assembly systems

Assembly processes play a big role in the current business context as global supply chains depend on many subcomponents to produce a single finished product. Previous studies have shown contrasting results regarding the effect that supply variability (the variability of feeding stations) has on the performance of assembly systems, as opposed to the variability of the station matching and assembling the components. This paper aims to close this gap by studying the behaviour of simple assembly systems with differing degrees of variability allocation among the stations through an experimental simulation study. Results suggest that a reduction in feeding station variability results in higher throughput, even in systems where the variability of one of the feeding stations increases while the other decreases. Furthermore, in scenarios with high total variance, the highest throughput is reached by transferring both variance and work from one of the feeding stations to any other station, whereas in low variance systems symmetrical work transfer to the feeding stations results in the highest throughput, as previously shown. Finally, reducing feeding station variability decreased the time spent in the assembly station (waiting time for component matching plus time for the assembly operation) only in experiments with high total variance.

The decision-making framework for assembly tasks planning in human–robot collaborated manufacturing system

ABSTRACT A human–robot collaborative assembly system is a new production paradigm, which has been successfully applied in practical production to effectively combine human flexibility and robot productivity. This paper proposes the task planning problem for human and robot collaboration and considers the whole process from assembly task decomposition, assembly to human and robot, and operations scheduling in hybrid assembly systems. The decision-making framework for the task planning problem is first introduced from five steps: data input, task decomposition, resource evaluation, operation allocation and scheduling, and collaborative assembly implementation. The task decomposition process is performed based on the hierarchical task analysis approach. The assembly operation allocation and scheduling are then considered in an integrated way, and the joint optimization model is developed considering the assembly operation sequence and the collaboration of humans and robots. Triple objectives are considered not only to minimize the competition time and total production costs but also to improve the automation degree of the hybrid system. The improved heuristic algorithm is developed to address the joint optimization problem. Finally, the application of this decision-making framework is described and verified based on two industrial cases. Computational results are presented to show the performance and feasibility of the proposed methodology.