Reliable capacity planning despite uncertain disassembly, regeneration and reassembly workloads by using statistical and mathematical approaches - Validation in subsidiaries of a global MRO company with operations in Asia, Europe and North America

The MRO industry faces substantial challenges with regard to the capacity planning of disassembly and reassembly work. This is due to the unknown workloads when regenerating complex investment goods and is caused, in particular, by the uncertain degree of disassembly and the complex challenges of reassembly. Forecasting techniques based on Bayesian networks are developed along with mathematical models which optimize capacity utilization, job order and the resulting costs. The approaches are tested and validated in conjunction with an MRO company with global operations. The results show possibilities for enhancing the planning processes and are found to be transferable on an international scale regardless of sociocultural and process differences.DFG/CRC/87

Improving MRO order processing by means of advanced technological diagnostics and data mining approaches

Production planning based on uncertain load information may lead to low schedule adherence or low capacity utilization. Thus, maintenance, repair and overhaul (MRO) service providers are striving to improve their business processes to achieve high logistics efficiency. To estimate repair expenditures and material demands as early as possible, different approaches may be pursued. In this paper, the advancement of technological diagnostics to enable condition assessment without prior disassembly and the use of data mining to generate reliable forecasts are discussed. Thereby, the potential for planning MRO order processing is focused using the example of aircraft engines and rail vehicle transformers

Model-based Analysis of Reassembly Processes within the Regeneration of Complex Capital Goods

In regenerating complex capital goods two of the key criteria for success on the market include keeping downtimes to a minimum in order to realize short throughput times and maintaining a high degree of schedule reliability. When unable to comply with the market's demands on their logistical performance, companies that provide regeneration services are faced with significant financial penalties and costs for delays as well as the threat of customers switching to competitors. In addition, regeneration processes must be economically effective. Efficiently designing and planning the entire regeneration process is therefore indispensable. As a core element, the reassembly at the end of the process chain plays a key role. Since the various material flows merge together here, the logistic quality of the supply processes is particularly visible at this point. Furthermore, reassembly is generally the last value-adding process within the regeneration supply chain. Up until now, descriptive and analytical approaches consider the various supply processes independently of one another and ignore to some degree existing statistical dependencies between these processes. These dependencies however, are frequently found in the industry and have to be taken into consideration when planning tasks and evaluating design measures. This paper will thus introduce the different existing approaches for describing and analyzing reassembly processes and compare them using a case study

Employ sensor fusion techniques for determining aircraft attitude and position information

Inertial Navigation Systems (INS) with the level of precision needed for Unmanned Aerial Vehicles (UAV) can easily cost more than the vehicle itself. This drastically increases the amount of aircraft power consumption and payload weight that drives the need for a low cost solution. This can be achieved through the use of sensor fusion techniques on low cost accelerometers and gyroscopes fused with Global Positioning System (GPS) data. In this paper, existing GPS and Inertial Measurement Unit (IMU) flight data is fused with the use of both an Kalman filter (KF) and Extended Kalman filter (EKF) methods for a more accurate estimate of the aircraft attitude, velocity, and position eliminating the need for the high cost attitude sensors. A simulation study shows that four sensor fusion methods verifying that an improvement of position, velocity, and attitude can be achieved using low-cost sensors. The first method incorporates a six state KF that corrects INS/GPS position and velocity errors. The second method features the GPS to estimate attitude parameters, which in turn uses in an EKF to correct INS attitude values. With this method, improved attitude values are obtained without the calculation of the full INS state; such that the INS position and velocity are not required, reducing the computational load. The third method uses only the GPS and INS position and velocity to correct for the errors in the full state of the INS also using an EKF. Finally, the last method combines the GPS attitude of the second method and the error reduction of the third method to further decrease the error in the velocity, position, and attitude of the system. The simulation results illustrate that all of the methods tested provide performance improvement to the system, and could be implemented in real-time on a UAV for accurate navigation parameters

Proceedings of the Conference on Production Systems and Logistics: CPSL 2022

[no abstract available

Proceedings of the 2nd Conference on Production Systems and Logistics (CPSL 2021)

Proceedings of the CPSL 202

Construction management abstracts : cumulative abstracts and indexes of journals in construction management, 1983-2000

The purpose of this document is to provide a single source of reference for every paper published in the journals directly related to research in Construction Management. It is indexed by author and keyword and contains the titles, authors, abstracts and keywords of every article from the following journals: • Building Research and Information (BRI) • Construction Management and Economics (CME) • Engineering, Construction and Architectural Management (ECAM) • Journal of Construction Procurement (JCP) • Journal of Construction Research (JCR) • Journal of Financial Management in Property and Construction (JFM) • RICS Research Papers (RICS) The index entries give short forms of the bibliographical citations, rather than page numbers, to enable annual updates to the abstracts. Each annual update will carry cumulative indexes, so that only one index needs to be consulted

Attitudes of Students and Practitioners Regarding Ethical Acceptability of Accounting Transactions

This study reports the findings of a study assessing the acceptability differences in decisions made by Certified Public Accounting practitioners (CPA) and students studying to become CPAs. The study responds to researchers’ call for additional research on topics related to accounting decision ethics. Modified managerial and accounting recognition scenarios were used to collect the acceptability of ethical judgments. The analysis employs factor analysis to affirm whether the scenarios are mana­gerial or accounting recognition decisions. The analyses further divides the managerial decisions into either revenue or expense related. The accounting recognition decisions are further divided into those involving an accounting manipulation or inventory related. Students’ acceptability of the accounting transactions was far harsher than the practitioners. However, both students and practitioners considered the accounting scenarios to be unethical. Both students and practitioners judged the managerial revenue scenarios to be ethical but the managerial expense scenarios to be moderately unethical. In addition to the ethical acceptability of accounting transaction, student and practitioner demographic data including age, work experience and academic credentials are investigated to explain the differences