H Luo

A case of implementing RFID-based real-time shop-floor material management for household electrical appliance manufacturers

Radio Frequency Identification (RFID) technologies provide automatic and accurate object data capturing capability and enable real-time object visibility and traceability. Potential benefits have been widely reported for improving manufacturing shop-floor management. However, reports on how such potentials come true in real-life shop-floor daily operations are very limited. As a result, skeptics overwhelm enthusiasm. This paper contributes to the re-vitalization of RFID efforts in manufacturing industries by presenting a real-life case study of applying RFID for managing material distribution in a complex assembly shop-floor at a large air conditioner manufacturer. The case study discusses how technical, social and organizational issues have been addressed throughout the project within the company. It is hoped that insights and lessons gained be generalized for future efforts across household electrical appliance manufacturers that share similar shop-floor.

Synchronisation of production scheduling and shipment in an assembly flowshop

This paper studies a synchronised scheduling problem of production simultaneity and shipment punctuality in a two-stage assembly flowshop system. Production simultaneity seeks to ensure all products belonging to a same customer order are simultaneously completed (at least as close as possible). Shipment punctuality attempts to satisfy orders’ individual shipment due dates. We provide two criteria, i.e. mean longest waiting duration and mean earliness and tardiness, for measuring production simultaneity and shipment punctuality, respectively. A synchronised scheduling model is developed by balancing the two criteria using linear weighted sum method. A modified genetic algorithm (GA) is then proposed for solving this model. Numerical studies demonstrate the effectiveness of the proposed approach. The results indicate that considering production simultaneity can remarkably reduce finished products inventory. A prioritised weight combination interval for production simultaneity and shipment punctuality has been suggested. Production simultaneity is affected by the production system configuration, especially in peak seasons.

Hybrid flowshop scheduling with batch-discrete processors and machine maintenance in time windows

This research considers a two-stage hybrid flowshop scheduling problem with challenging characteristics substantiated by the complexity of the problem in a collaborating company. Multiple (three) parallel machines are involved in the first stage and only one machine in the second stage. Stage 1 parallel machines are able to process multiple jobs simultaneously but the jobs must be sequentially setup one after another with the loading time depending on the processing time of the stage 2 machine. A blocking environment exists between the two stages with no intermediate buffer storage. In order to reduce the complexity, multiple simultaneous jobs are grouped into batches according to their similarities. Batches can then be considered as basic units for scheduling to determine which stage 1 machine and in what sequence batches are loaded. A genetic algorithm is used to obtain near-optimal schedules mainly by minimising the makespan. The proposed model and solution algorithm are applied to solve the problem in the collaborating company under a set of complicated rules and constraints. Comprehensive studies are conducted with real-life data. The results are consistent with the companys operational principles and are superior compared with the manual schedules.

Cloud-enabled real-time platform for adaptive planning and control in auction logistics center

Key components and decisions of a typical auction logistics center are discussed associated with related management issues.Based on cloud computing and internet of things technologies, auction logistics reengineering is conducted.The referenced infrastructure of CALC is elaborated for planning and control services at the ALC.The implementation and application methods of CALC are described in a case study.Lessons learnt through the deployment are also presented. An auction logistics center (ALC) is the facility that is dedicated to all logistics and physical distribution, and provides auction functions for goods trading. Adaptive planning and control has been a hot research topic and discussed a lot in the field of manufacturing. Adaptive auction logistics planning and control (ALPC) is urgently required at the ALC to support large trading volumes and shorten processing time. To solve real-life industrial challenges, this paper presents a generic system architecture and its implementation along with the following dimensions. Firstly, a cloud-enabled platform for auction logistics center (CALC) is presented. It is proposed to implement efficient and effective ALPC, and to increase the flexibility in terms of execution of logistics operations and auction processes. Secondly, through the integration of IoT (Internet of Things) and cloud computing technologies, the proposed CALC creates a ubiquitous environment at the ALC, and establishes auction logistics services for different key stakeholders. The adaptive ALPC can be achieved with real-time visibility and traceability. Finally, this study presents a prototype of CALC to verify the proposed methodology. The case study in this paper also shows the potential of CALC to streamline operating processes in auction logistics environment.

Real-time scheduling for hybrid flowshop in ubiquitous manufacturing environment

Implementation of RFID technologies for real-time planning and scheduling.Ubiquitous manufacturing (UM) environment created in shop floor.Multi-period hierarchical scheduling mechanism.Two users hierarchically make decisions for their own objectives. This paper discusses the implementation of RFID technologies, which enable the shop floor visibility and reduce uncertainties in the real-time scheduling for hybrid flowshop (HFS) production. In the real-time HFS environment, the arriving of new jobs is dynamic, while the processes in work stages are not continuous. The decision makers in shop floor level and stage level have different objectives. Therefore, classical off-line HFS scheduling approaches cannot be used under these situations. In this research, two major measures are taken to deal with these specific real-time features. Firstly, a ubiquitous manufacturing (UM) environment is created by deploying advanced wireless devices into value-adding points for the collection and synchronization of real-time shop floor data. Secondly, a multi-period hierarchical scheduling (MPHS) mechanism is developed to divide the planning time horizon into multiple shorter periods. The shop floor manager and stage managers can hierarchically make decisions for their own objectives. Finally, the proposed MPHS mechanism is illustrated by a numerical case study.

Active scheduling for hybrid flowshop with family setup time and inconsistent family formation

This research is motivated by a real-life hybrid flowshop scheduling problem where jobs are organized in families according to their machine settings and tools. This type of problem is common in the production process of standard metal components. The problem is complicated by the requirement of family setup time when a machine changes from processing one job family to another and the formation of job families varies in different stages. This problem has been previously solved with a non-delay scheduling heuristic in which no machine is kept idle. This research illustrates that inserting intentional idle time into a non-delay schedule can further reduce the total setup time as well as makespan. With the inserted idle time, the non-delay schedules are extended to active schedules. This paper presents a mechanism to determine the locations and lengths of intentional idle times in the efficient active schedules. Four active scheduling approaches are developed by integrating two types of waiting factor operators into two non-delay approaches. Computational experiments have been conducted to compare the proposed active scheduling approaches in terms of effectiveness and efficiency. The results have shown that the proposed active scheduling approaches are superior to non-delay scheduling. The analysis of variance has been applied on the factors related to scheduling environment, problem size and scheduling approach. The analysis has identified factors that are most influential on the scheduling result.

Hybrid flowshop scheduling with family setup time and inconsistent family formation

This research considers a hybrid flowshop scheduling problem where jobs are organised in families according to their machine settings and tools. The family setup time arises when a machine shifts from processing one job family to another. The problem is compounded by the challenges that the formation of job families is different in different stages and only a limited number of jobs can be processed within one setup. This type of problem is common in the production process of standard metal components. This paper aims to propose two approaches to solve this problem. One is a metaheuristic in the form of a genetic algorithm and the other is a heuristic. The proposed approaches are compared and contrasted against the two relevant metaheuristic and heuristic adapted from solving a generalised sequence-dependent setup flowshop problem. Comparative results indicate that the proposed genetic algorithm has better performance on minimising makespan and the heuristic is more effective on reducing family setup time.

Internet-of-Things-Enabled Smart Production Logistics Execution System Based on Cloud Manufacturing

With the rapid development of cloud computer concept and technologies, more and more cloud-based business mode and practical applications are emerging in industrial environments, including cloud manufacturing and cloud logistics. Such cloud systems integrate the distributed resources and make best use of them to fulfill dynamic tasks in an optimal way. This paper will demonstrate a simple yet practical application of a cloud-based production logistics (PL) management system (C-PLES) developed under Internet-of-Things (IoT) environment. It collects both real-time process dynamics and resource statues from a ubiquitous PL environment to realize dynamic distributed capability matching. The systematic combination of IoT and cloud system enables the distributed PL terminal resources with uncertainties (e.g. availabilities and locations) to be optimally accessed and assigned to fulfill the real-time PL requirements generated from the dynamic production processes. It also enables the distributed execution data to be centrally managed and seamlessly switched among the dynamically accessed resources.Copyright

Cloud service-oriented dashboard for work cell management in RFID-enabled ubiquitous manufacturing

This article aims at developing a service-oriented dashboard for operators and supervisors of manufacturing shopfloor work-cells to realize information visibility and traceability effectively with cloud and RFID (radio frequency identification) technologies. The work is based on a case of an illustrative assembly line consisting of a number of work cells. The dashboard is deployed for facilitating assembly operations in ubiquitous manufacturing environment. The utilization of the system leads to significant improvements in work cell productivity and quality, operational flexibility and decision efficiency.

RFID-enabled smart assembly workshop management system

Although RFID technologies are enjoying rapid developments, its practical use in manufacturing processes is still limited. Existed applications focus mainly on the pallet-level RFID implementation, which facilitates batch data processing in material handling operations, e.g. material delivery, yet cannot realize real-time lean control for individual parts. This leaves the manufacturing processes as a blank area for taking full advantages of RFID. This paper discusses the item-level RFID implementation in terms of both real-time information control mechanism and system development. A simulated automobile assembly line is employed for concept demonstration. Three questions will be addressed. First, how to use RFID systems to enable the real-time coordination and interaction between the production planning and execution levels to achieve the lean control of manufacturing processes. Second, how to realize the RFID-enabled smart management for typical manufacturing processes, including assembling, packaging, buffering, etc. Thirdly, how to establish a real-time information infrastructure to integrated the typical RFID-enabled smart processes.