International Journal of Industrial Engineering: Theory, Applications and Practice
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Web-Enabled Vision Guided Robotic Tracking Within the Framework of E-Manufacturing
Get PDFThe current trends in industry include an integration of information and knowledge base network with a manufacturing system, which coined a new term, E-Manufacturing. From the perspective of E-Manufacturing, any production equipment and its control functions do not exist alone, but become a part of the holistic operation system with distant monitoring, remote quality control and fault diagnostic capabilities. The key to this new paradigm is the accessibility to a remotely located system and having the means of responding to a changing environment, which is better suited for today’s rapidly changing environment. In this context, this paper presents an innovative method in part tracking using the Ethernet SmartImage Sensor and the web-controllable SCARA robot. Remote controlling of an automation process using Internet can suffer from time lag, if the network is congested with heavy data traffic, which maybe the greatest hurdle for using Internet for real time control. The approach discussed in this paper overcomes the time lag for part tracking and mathematically calculates the product locations on the conveyor at various instances and efficiently guide the robot to the product. The accuracy of the proposed scheme has been verified, which vindicates the industrial applicability of the setup. The web-enabled robotic operations present many benefits, such as ubiquitous access, remote control, programming, monitoring capabilities, and integration of production equipment into information networks for improved efficiency and quality
When Customer Specifications for a Product Lie Outside a Product's Material Properties and Process Capability - A Case Study
Get PDFTo avoid losing a $12M client, a vendor addressed complaints that their disposable baby bottle liners failed hot water pressure tests and had widths outside specifications. The prescribed resin’s softening point was (980C (208.40F)). At the vendor’s testing site (580 meters above sea level) water boils at 97.20C (2070F). At the client laboratory (11 meters above sea level) water boils at 99.40C (2110F). Thus liners that met vendor specifications failed at the client’s laboratory. An alternative resin (softening point: 1070C (2230F)) was found to met client specification. A process capability study revealed that the machines were incapable of producing liners to client specifications. Further investigation revealed that the complaints related to problems customers had extracting liners from the package. An out-of-round packaging core provided by another vendor was the cause of uneven extraction. Changing resins and ensuring cores were in-round resulted in meeting the client’s quality concerns
A FUZZY BI-LEVEL PROJECT PORTFOLIO PLANNING CONSIDERING THE DECENTRALIZED STRUCTURE OF PHARMACY HOLDINGS
Get PDFResearch and development (R&D) in the pharmaceutical industry requires proper and optimal planning and management because of its critical role in public health. Taking into account a decentralized decision-making structure in R&D management in pharmaceutical holding companies, this study introduces a new fuzzy bi-level multi-follower mathematical optimization model to address budget allocation and project portfolio planning. Specifically, the holding company's head office, as the leader, and the subsidiaries, as followers, make strategic and operational decisions concerning important issues such as budget allocation and portfolio selection and scheduling. Since the lower level represents multiple mixed-integer programming problems with uncooperative reference relationships between followers, solving the resulting bi-level model is challenging. Therefore, our model is based on an effective hybrid solution methodology, which converts the bi-level model, including multiple followers, into a single-level model. In order to validate the proposed model, we conducted a case study and analyzed the strategies of each actor within the conglomerate. Based on the results of experiments, it is evident that a strategy that focuses on one level of operations profoundly affects decisions at the other level
The Development of a Training Expert System for TFT-LCD Defects Inspection
Get PDFAt present, the image quality of LCD panels has been determined subjectively by human visual inspection. In fact, the inspectors need to memorize a large number of instructions. The inspection tasks include a series of complicated procedures that increase the workload of the inspectors. This research focuses on the improvement of LCD inspection. The knowledge extracting of inspection data was to analyze association rules through interviewing experienced inspectors. Then the nested IF-THEN inspection rules between defects and test patterns were analyzed by two-dimensional matrix and group technology (GT). In terms of inspection test patterns, the occurring sequence of pattern was rearranged to make inspection tasks more efficient. Furthermore, this study aimed to construct an expert system for LCD defects inspection. According to the results of the experiment and expert evaluation, the expert system was proposed as a training support system to aid the trainees to learn inspection skills more effectively. Therefore, the performance of the inspection training could be improved
PREDICTIVE DESIGN OF THE F-POLICY MARKOVIAN QUEUE
No full textWe consider in this paper the queueing model under the policy. In this system, customers are denied entry when the system is full, until the queue size drops to the level , following the departure of served customers. To start the admission of customers again, a startup job is required for the server. Since the goal of the F-policy is to gain control over the system, we propose an approach that selects the optimal system parameters. Numerical examples validate the theoretical results obtained
A NOVEL SUPPLIER SELECTION APPROACH BASED ON EXTENDED DATA ENVELOPMENT ANALYSIS UNDER A HESITANT FUZZY LINGUISTIC ENVIRONMENT
No full textSupplier selection is a core supply chain issue. Choosing suitable suppliers will directly affect the success and sustainable development of the overall supply chain. Further, the assessment criteria of supplier selection include qualitative and quantitative assessment factors simultaneously. Thus, experts may give assessment criteria scores that include hesitant fuzzy information or incomplete information. These factors make the problem of choosing the right suppliers more complicated. The traditional average value approach and the traditional data envelopment analysis (DEA) method can only handle complete assessment criteria score information given by experts. They cannot simultaneously handle complete information, incomplete information, and hesitant information in the supplier selection process. In order to further handle this issue, this paper proposed a novel supplier selection approach based on extended DEA under a hesitant fuzzy linguistic (HFL) environment. The innovation of the proposed method lies in its capacity to simultaneously process complete information, incomplete information, and hesitant information in the supplier selection process. Furthermore, it can effectively solve a high number of duplicated DEA values of 1 for the DEA method. An illustrative example of consultant company selection was used to verify the rationality and correctness of the proposed approach. This study also compares the simulation results of the traditional average value method and the DEA method with those achieved using the proposed approach. The numerical test results show that the proposed approach can handle the above supplier selection issues under an HFL environment
RIDESOURCING IN MANUFACTURING SITES: A FRAMEWORK AND CASE STUDY
Get PDFWith the recent innovations in transportation, ridesourcing services have been proliferating in many countries. There are increasing attempts to apply ridesourcing in the corporate context. Manufacturing companies now install the Industrial Internet of Things (IIOT) sensors to vehicles to obtain real-time data on the movement of goods and materials. Despite the massive amount of data accumulated, little attention has been paid to exploiting the data for vehicle fleet management (FM). This paper proposes an analytical framework to solve two FM problems: how to group organizational units for vehicle sharing and where to deploy the groups. The framework is then validated with a case study of a Korean shipbuilder. The results indicate that grouping departments with similar spatial patterns can reduce the current fleet
Simulated Annealing for Solving Piecewise Linear Supplier Selection Problem Considering Quantity Discounts
Get PDFSupplier selection problems are often complicated due to the conflicting objectives and constraints that need to be considered while selection. This problem becomes still more complicated with the inclusion of quantity discounts offered by the suppliers. A multi component multiple supplier selection model considering quantity discounts under incremental quantity discount scenario is proposed in this paper. The combinatorial nature of the supplier selection problem motivates to explore the use meta-heuristic algorithm for solving this complex problem. The proposed model is evaluated using simulated annealing in this article. The results were found to be near optimal along with the generation of alternate set of solutions. Such type of solutions will be very useful to manufacturing firm where the purchase manager would also like to look at options for alternative solutions
Optimization Approach to Hazard Prevention Budgeting Problem
Get PDFAn analytical approach to optimally allocate the hazard prevention budget so as to eliminate or reduce hazard exposures in the industrial workplace is presented. Two hazard control approaches are considered: engineering approach and administrative approach. For the engineering approach, we consider controlling at the source of hazard and blocking the hazard along the transmission path. For the administrative approach, only job rotation is considered. From the given hazard prevention budget, four optimization models are sequentially employed to select appropriate hazard controls without exceeding the allocated budget. A sensitivity analysis is performed to study how the hazard prevention solution is affected by the budget portion allocated to engineering controls
A Revised Version of Ant Colony Algorithm for One-Dimensional Cutting Stock Problem
Get PDFThe one-dimensional cutting stock problem has many applications in industries and during the past few years has been one of the centers of attention among the researchers in the field of applied operations research. In this paper, a revised version of Ant Colony Optimization (ACO) technique is presented to solve this problem. This paper is a sequel to the previous ACO algorithm presented by the authors. In this algorithm, according to some probabilistic rules, artificial ants will select cutting patterns and generate a feasible solution. Computational results show the high efficiency and accuracy of the proposed algorithm for solving one- dimensional cutting stock problem