The optimisation and integration of AGVs with the manufacturing process

In recent years, the manufacturing environment, driven by the growth of advanced technologies and the increasing demand for customised products, has becomes increasingly competitive. In this context, manufacturing systems are now required to be more automated, flexible and reconfigurable. Thus, Autonomous Guided Vehicle (AGV), as a key enabler of dynamic shop floor logistics, are being increasingly widely deployed into the manufacturing sector for the lineside materials supplying, work-in-progress transportation, and finished products collection. A large number of companies and institutions are researching on different AGV systems to integrate AGVs-based shop floor logistics with manufacturing equipment and processes. However, these AGV systems are typically equipped with various communication protocols and utilise ad-hoc communication methods. They lack a generic framework to integrate the AGV systems into the manufacturing systems with minimal engineering effort and system reconfiguration. Current scheduling optimisation methods for multiple AGVs in shop floor logistics now support effective task allocation, shortest route planning, and conflict-free supervision, allocating the delivery tasks based on the location and availability of AGVs. However, these current methods do not give enough consideration to real-time operational information during the manufacturing process and have difficulties in analysing the real-time delivery requests from manufacturing work stations. This not only reduces the efficiency and flexibility of the shop floor logistics, ii but also significantly impacts on the overall performance of manufacturing processes. This thesis presents a generic integration approach, called Smart AGV Management System (SAMS), to support the integration of AGVs with manufacturing processes. The proposed framework enables enhanced interoperability between AGVs-based shop floor logistics and the manufacturing process through a generic data-sharing platform. Moreover, a Digital Twin (DT)-based optimisation method is developed in SAMS that can simulate and analyse the real-time manufacturing process to schedule AGVs for optimising multiple objectives, including the utilisation of work stations, delivery Justin- time (JIT) performance, charging of AGVs and overall energy consumption. This approach is experimentally deployed and evaluated from various perspectives to identify its integration and optimisation capabilities during the reconfiguration and operational phases. The results show that the proposed integration framework can enable a more effective integration with manufacturing process compared to traditional integration methods. In addition, the results demonstrate that the proposed optimisation method can schedule and reschedule AGV-based shop floor logistics when facing a range of system disruptions

Improving just-in-time delivery performance of IoT-enabled flexible manufacturing systems with AGV based material transportation

Autonomous guided vehicles (AGVs) are driverless material handling systems used for transportation of pallets and line side supply of materials to provide flexibility and agility in shop-floor logistics. Scheduling of shop-floor logistics in such systems is a challenging task due to their complex nature associated with the multiple part types and alternate material transfer routings. This paper presents a decision support system capable of supporting shop-floor decision-making activities during the event of manufacturing disruptions by automatically adjusting both AGV and machine schedules in Flexible Manufacturing Systems (FMSs). The proposed system uses discrete event simulation (DES) models enhanced by the Internet-of-Things (IoT) enabled digital integration and employs a nonlinear mixed integer programming Genetic Algorithm (GA) to find near-optimal production schedules prioritising the just-in-time (JIT) material delivery performance and energy efficiency of the material transportation. The performance of the proposed system is tested on the Integrated Manufacturing and Logistics (IML) demonstrator at WMG, University of Warwick. The results showed that the developed system can find the near-optimal solutions for production schedules subjected to production anomalies in a negligible time, thereby supporting shop-floor decision-making activities effectively and rapidly

Effects of Bufei Yishen Granules Combined with Acupoint Sticking Therapy on Pulmonary Surfactant Proteins in Chronic Obstructive Pulmonary Disease Rats

Our previous studies have demonstrated the beneficial effects of Bufei Yishen granules combined with acupoint sticking therapy (the integrated therapy) in chronic obstructive pulmonary disease (COPD), but the underlying mechanism remains unclear. Dysfunction of pulmonary surfactant proteins (SPs, including SP-A, SP-B, SP-C, and SP-D) may be included in pathophysiology of COPD. This study aimed to explore the mechanism of the integrated therapy on SPs. COPD rat models were established. The treatment groups received Bufei Yishen granules or acupoint sticking or their combination. Using aminophylline as a positive control drug. The levels of SPs in serum, BALF, and lung were measured. The results showed that the integrated therapy markedly reduced the levels of SPs in serum and increased these indicators in the lung. The integrated therapy was better than aminophylline in reducing the levels of SPs and was better than Bufei Yishen granules in reducing SP-A, SP-C, and SP-D in serum. The integrated therapy was better than aminophylline and Bufei Yishen granules in increasing SP-A, SP-B, and SP-D mRNA in the lung. SP-A and SP-D in BALF were positively correlated with PEF and EF50. The levels of SPs are associated with airway limitation. The beneficial effects of the integrated therapy may be involved in regulating pulmonary surfactant proteins