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

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

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. 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

Cost Factor Focused Scheduling and Sequencing: A Neoteric Literature Review

The hastily emergent concern from researchers in the application of scheduling and sequencing has urged the necessity for analysis of the latest research growth to construct a new outline. This paper focuses on the literature on cost minimization as a primary aim in scheduling problems represented with less significance as a whole in the past literature reviews. The purpose of this paper is to have an intensive study to clarify the development of cost-based scheduling and sequencing (CSS) by reviewing the work published over several parameters for improving the understanding in this field. Various parameters, such as scheduling models, algorithms, industries, journals, publishers, publication year, authors, countries, constraints, objectives, uncertainties, computational time, and programming languages and optimization software packages are considered. In this research, the literature review of CSS is done for thirteen years (2010-2022). Although CSS research originated in manufacturing, it has been observed that CSS research publications also addressed case studies based on health, transportation, railway, airport, steel, textile, education, ship, petrochemical, inspection, and construction projects. A detailed evaluation of the literature is followed by significant information found in the study, literature analysis, gaps identification, constraints of work done, and opportunities in future research for the researchers and experts from the industries in CSS

A Coloured Petri Net- and D* Lite-Based Traffic Controller for Automated Guided Vehicles

Mobile robots, such as Automated Guided Vehicles (AGVs), are increasingly employed in automated manufacturing systems or automated warehouses. They are used for many kinds of applications, such as goods and material handling. These robots may also share industrial areas and routes with humans. Other industrial equipment (i.e., forklifts) could also obstruct the outlined routes. With this in mind, in this article, a coloured Petri net-based traffic controller is proposed for collision-free AGV navigation, in which other elements moving throughout the industrial area, such as humans, are also taken into account for the trajectory planning and obstacle avoidance. For the optimal path and collision-free trajectory planning and traffic control, the D* Lite algorithm was used. Moreover, a case study and an experimental validation of the suggested solution in an industrial shop floor are presented

Scheduling of Multiple Autonomous Guided Vehicles for an Assembly Line Using Minimum Cost Network Flow

This paper proposed a parallel automated assembly line system to produce multiple products having multiple autonomous guided vehicles (AGVs). Several assembly lines are configured to produce multiple products in which the technologies of machines are shared among the assembly lines when required. The transportation between the stations in an assembly line (intra assembly line) and among stations in different assembly lines (inter assembly line) are performed using AGVs. Scheduling of AGVs to service the assembly lines and the corresponding stations are purposed. In the proposed problem the assignment of multiple AGVs to different assembly lines and the stations are performed using minimum-cost network flow (MCF). It optimizes weighted completion time of tasks for each short-term window by formulating the task and resource assignment problem as MCF problem during each short-term scheduling window. <br /

Order Picking Problem: A Model for the Joint Optimisation of Order Batching, Batch Assignment Sequencing, and Picking Routing

Background: Order picking is a critical activity in end-product warehouses, particularly using the picker-to-part system, entail substantial manual labor, representing approximately 60% of warehouse work. Methods: This study develops a new linear model to perform batching, which allows for defining, assigning, and sequencing batches and determining the best routing strategy. Its goal is to minimise the completion time and the weighted sum of tardiness and earliness of orders. We developed a second linear model without the constraints related to the picking routing to reduce complexity. This model searches for the best routing using the closest neighbour approach. As both models were too complex to test, the earliest due date constructive heuristic algorithm was developed. To improve the solution, we implemented various algorithms, from multi-start with random ordering to more complex like iterated local search. Results: The proposed models were tested on a real case study where the picking time was reduced by 57% compared to single-order strategy. Conclusions: The results showed that the iterated local search multiple perturbation algorithms could successfully identify the minimum solution and significantly improve the solution initially obtained with the heuristic earliest due date algorithm

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

Planning and control of autonomous mobile robots for intralogistics: Literature review and research agenda

Autonomous mobile robots (AMR) are currently being introduced in many intralogistics operations, like manufacturing, warehousing, cross-docks, terminals, and hospitals. Their advanced hardware and control software allow autonomous operations in dynamic environments. Compared to an automated guided vehicle (AGV) system in which a central unit takes control of scheduling, routing, and dispatching decisions for all AGVs, AMRs can communicate and negotiate independently with other resources like machines and systems and thus decentralize the decision-making process. Decentralized decision-making allows the system to react dynamically to changes in the system state and environment. These developments have influenced the traditional methods and decision-making processes for planning and control. This study identifies and classifies research related to the planning and control of AMRs in intralogistics. We provide an extended literature review that highlights how AMR technological advances affect planning and control decisions. We contribute to the literature by introducing an AMR planning and control framework t

Autonomous Unmanned Ground Vehicles for Urban Logistics: Optimization of Last Mile Delivery Operations

In an era dominated by ongoing urbanization and rising e-commerce, the efficient delivery of goods within cities becomes a major challenge. As a new element of urban logistics, we discuss the potential of autonomous unmanned ground vehicles (AUGV) regarding the last mile delivery of shipments to customers. We propose an optimization model to minimize the delivery costs of urban shipments using AUGV. Simultaneously, best locations from a set of existing stations are selected for AUGV positioning and optimal route determination. With our developed Location Routing Problem, we provide decision support for parcel service providers, city authorities, and other relevant decision makers. Regarding the Green Information Systems domain, we tackle the lack of solution-oriented research addressing a more sustainable and locally emission free supply of goods within urban areas

A research survey: review of flexible job shop scheduling techniques

In the last 25 years, extensive research has been carried out addressing the flexible job shop scheduling (JSS) problem. A variety of techniques ranging from exact methods to hybrid techniques have been used in this research. The paper aims at presenting the development of flexible JSS and a consolidated survey of various techniques that have been employed since 1990 for problem resolution. The paper comprises evaluation of publications and research methods used in various research papers. Finally, conclusions are drawn based on performed survey results. A total of 404 distinct publications were found addressing the FJSSP. Some of the research papers presented more than one technique/algorithm to solve the problem that is categorized into 410 different applications. Selected time period of these research papers is between 1990 and February 2014. Articles were searched mainly on major databases such as SpringerLink, Science Direct, IEEE Xplore, Scopus, EBSCO, etc. and other web sources. All databases were searched for &ldquo;flexible job shop&rdquo; and &ldquo;scheduling&rdquo; in the title an