An investigation into manual labour reporting within South African Airways Technical

M.B.A.This study is concerned with an investigation into the manual labour reporting system as currently operated by South African Airways (SAA) Technical. This was necessary, as a large percentage of the time sheet hours were not being captured with the net result being that costs and the resultant effects were becoming distorted. The primary purposes of this research was to identify the reasons for the current difficulties being experienced with labour cost recovery within SAA Technical in order to propose changes to rectify the impasse. The following reasons for the labour hour losses were identified: • Ineffective operational control methods. • Deployment of geographically dispersed data capturers. • Computer programming errors in the transfer routines. These problems naturally lead to a loss of control. The following improvements after rectification were noticeable: • In January 1997, average labour hour under recovery was as high as 46%. After rectification, losses were down to 15% (cf. 4.3). • The management accounting reporting document was greatly revised; thus rendering improved service to and understanding by the users. • The automated labour reporting bar scanning system currently being implemented would also benefit from the rectified computer transfer program. It may thus be concluded that the research was beneficial to SAA Technical operation and provided solid reasons for the labour hour losses. If the recommendations as presented further on in this study are adhered to, there should be no reason for the present situation not to maintain or improve the current improvements

Glossary of Software Engineering Laboratory terms

A glossary of terms used in the Software Engineering Laboratory (SEL) is given. The terms are defined within the context of the software development environment for flight dynamics at the Goddard Space Flight Center. A concise reference for clarifying the language employed in SEL documents and data collection forms is given. Basic software engineering concepts are explained and standard definitions for use by SEL personnel are established

Working Notes from the 1992 AAAI Spring Symposium on Practical Approaches to Scheduling and Planning

The symposium presented issues involved in the development of scheduling systems that can deal with resource and time limitations. To qualify, a system must be implemented and tested to some degree on non-trivial problems (ideally, on real-world problems). However, a system need not be fully deployed to qualify. Systems that schedule actions in terms of metric time constraints typically represent and reason about an external numeric clock or calendar and can be contrasted with those systems that represent time purely symbolically. The following topics are discussed: integrating planning and scheduling; integrating symbolic goals and numerical utilities; managing uncertainty; incremental rescheduling; managing limited computation time; anytime scheduling and planning algorithms, systems; dependency analysis and schedule reuse; management of schedule and plan execution; and incorporation of discrete event techniques

Random Keys Genetic Algorithms Scheduling and Rescheduling Systems for Common Production Systems

The majority of scheduling research deals with problems in specific production environments with specific objective functions. However, in many cases, more than one problem type and/or objective function exists, resulting in the need for a more generic and flexible system to generate schedules. Furthermore, most of the published scheduling research focuses on creating an optimal or near optimal initial schedule during the planning phase. However, after production processes start, circumstances like machine breakdowns, urgent jobs, and other unplanned events may render the schedule suboptimal, obsolete or even infeasible resulting in a rescheduling problem, which is typically also addressed for a specific production environment, constraints, and objective functions. This dissertation introduces a generic framework consisting of models and algorithms based on Random Keys Genetic Algorithms (RKGA) to handle both the scheduling and rescheduling problems in the most common production environments and for various types of objective functions. The Scheduling system produces predictive (initial) schedules for environments including single machines, flow shops, job shops and parallel machine production systems to optimize regular objective functions such as the Makespan and the Total Tardiness as well as non-regular objective functions such as the Total Earliness and Tardiness. To deal with the rescheduling problem, and using as a basis the same RKGA, a reactive Rescheduling system capable of repairing initial schedules after the occurrence of unexpected events is introduced. The reactive Rescheduling system was designed not only to optimize regular and non-regular objective functions but also to minimize the instability, a very important aspect in rescheduling to avoid shop chaos due to disruptions. Minimizing both schedule inefficiency and instability, however, turns the problem into a multi-objective optimization problem, which is even more difficult to solve. The computational experiments for the predictive model show that it is able to produce optimal or near optimal schedules to benchmark problems for different production environments and objective functions. Additional computational experiments conducted to test the reactive Rescheduling system under two types of unexpected events, machine breakdowns and the arrival of a rush job, show that the proposed framework and algorithms are robust in handling various problem types and computationally reasonable

Design and technological support for the manufacture of “Shaft Bearing Housing”

Design of work piece structure of shaft bearing housing deals economic calculation of new manufacturing part is already produce and the idea is to save money and increase production technological process implementation and to make manufacturing process better to reduce machining rejection, all mechanical work and design process standard operation to be done on it during the production process and all design activities covering this process

A methodology for implementing total productive maintenance in the commercial aircraft industry

Thesis (M.S.)--Massachusetts Institute of Technology, Sloan School of Management, 1996, and Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.Includes bibliographical references (p. 172-173).by Eugene C. Hamacher.M.S

The deep space network

Progress is reported in flight project support, tracking and data acquisition, research technology, network engineering, hardware and software implementation, and operations

Managerial cost accounting for a technical information center

Managerial cost accounting system for information retrieval center

Learning from systems failure : a case study application

Bibliography: leaves 255-258.The thesis as a whole concerns the identification and resolution organisational issues and details research that was undertaken in a manufacturing company producing light access equipment, Castor & Ladder incorporating Forlezer (C&L inc. rorlezer). The content itself is based on 'systems thinking' which endorses a holistic approach to problem solving - as opposed to the traditional reductionist or mechanistic approaches - and it is hoped to demonstrate the value of adopting a Systems Approach in resolving problems of an organisational nature. Particularly, the aim is to incorporate the consideration of underlying issues i.e. 'soft' problems pertinent to organisational dynamics, into a coherent and rigorous problem solving approach. In this regard, the approach taken focuses primarily on generating a holistic perception of the contextual 'problem situation' faced by the organisation. The view held is that in order to achieve effective solutions, a critical requirement is to first gain comprehensive understanding of the situation and its complexity. From a research perspective, the intention is to first enrich the perceived problem situation and then only to develop a concern (or hypothesis) that adequately presents the true issues at hand. Next, the aim is to develop the relevant theory applicable and necessary to the understanding and resolution of the situation, and to subsequently apply this theory to the context. In observing the outcome, the validity of the concern, as well as the theory is verified

Evolutionary algorithms for scheduling operations

While business process automation is proliferating through industries and processes, operations such as job and crew scheduling are still performed manually in the majority of workplaces. The linear programming techniques are not capable of automated production of a job or crew schedule within a reasonable computation time due to the massive sizes of real-life scheduling problems. For this reason, AI solutions are becoming increasingly popular, specifically Evolutionary Algorithms (EAs). However, there are three key limitations of previous studies researching application of EAs for the solution of the scheduling problems. First of all, there is no justification for the selection of a particular genetic operator and conclusion about their effectiveness. Secondly, the practical efficiency of such algorithms is unknown due to the lack of comparison with manually produced schedules. Finally, the implications of real-life implementation of the algorithm are rarely considered. This research aims at addressing all three limitations. Collaborations with DBSchenker,the rail freight carrier, and Garnett-Dickinson, the printing company,have been established. Multi-disciplinary research methods including document analysis, focus group evaluations, and interviews with managers from different levels have been carried out. A standard EA has been enhanced with developed within research intelligent operators to efficiently solve the problems. Assessment of the developed algorithm in the context of real life crew scheduling problem showed that the automated schedule outperformed the manual one by 3.7% in terms of its operating efficiency. In addition, the automatically produced schedule required less staff to complete all the jobs and might provide an additional revenue opportunity of £500 000. The research has also revealed a positive attitude expressed by the operational and IT managers towards the developed system. Investment analysis demonstrated a 41% return rate on investment in the automated scheduling system, while the strategic analysis suggests that this system can enable attainment of strategic priorities. The end users of the system, on the other hand, expressed some degree of scepticism and would prefer manual methods