Route planning of automated guided vehicles for container logistics

Automated guided vehicles (AGVs) are widely used in container terminals for the movement of material from shipping to the yard area and vice versa. Research in this area is directed toward the development of a path layout design and routing algorithms for container movement. The problem is to design a path layout and a routing algorithm that will route the AGVs along the bi-directional path so that the distance traveled will be minimized. This thesis presents a bi-directional path flow layout and a routing algorithm that guarantee conflict-free, shortest time routes for AGVs. Based on the path layout, a routing algorithm and sufficient, but necessary conditions, mathematical relationships are developed among certain key parameters of vehicle and path. A high degree of concurrency is achieved in the vehicle movement. The routing efficiency is analyzed in terms of the distance traveled and the time required for AGVs to complete all pickup and drop-off jobs. Numerical results are presented to compare performance of the proposed model. The research provides the foundation for a bi-directional path layout design and routing algorithms that will aid the designer to develop complicated path layouts

Technology Target Studies: Technology Solutions to Make Patient Care Safer and More Efficient

Presents findings on technologies that could enhance care delivery, including patient records and medication processes; features and functionality nurses require, including tracking, interoperability, and hand-held capability; and best practices

An overview of decision table literature 1982-1995.

This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.

Study of aircraft in intraurban transportation systems, volume 1

An analysis of an effective short range, high density computer transportation system for intraurban systems is presented. The seven county Detroit, Michigan, metropolitan area, was chosen as the scenario for the analysis. The study consisted of an analysis and forecast of the Detroit market through 1985, a parametric analysis of appropriate short haul aircraft concepts and associated ground systems, and a preliminary overall economic analysis of a simplified total system designed to evaluate the candidate vehicles and select the most promising VTOL and STOL aircraft. Data are also included on the impact of advanced technology on the system, the sensitivity of mission performance to changes in aircraft characteristics and system operations, and identification of key problem areas that may be improved by additional research. The approach, logic, and computer models used are adaptable to other intraurban or interurban areas

On the engineering of crucial software

The various aspects of the conventional software development cycle are examined. This cycle was the basis of the augmented approach contained in the original grant proposal. This cycle was found inadequate for crucial software development, and the justification for this opinion is presented. Several possible enhancements to the conventional software cycle are discussed. Software fault tolerance, a possible enhancement of major importance, is discussed separately. Formal verification using mathematical proof is considered. Automatic programming is a radical alternative to the conventional cycle and is discussed. Recommendations for a comprehensive approach are presented, and various experiments which could be conducted in AIRLAB are described

Data analytics and visualization for enhanced highway construction cost indexes and as-built schedules

A considerable amount of digital data is being collected by State Highway Agencies (SHAs) to aid project-planning activities, support various project level decision-making processes, and effectively maintain and operate constructed highway assets. However, the highway construction industry has been significantly lagging behind utilizing the growing digital data to support business decisions compared to other industry sectors such as health care and energy. The significant lack of understanding on the linkage between raw data collected and various decisions, proper computational methodologies, and effective guidance is considered as major barriers to the full utilization of the digital data. This study uses digital datasets that are now commonly available in SHAs, to demonstrate the smart utilization of existing digital data to support and enhance decision-making processes using data analytics and visualization methods. This study will a) develop an advanced computational methodology to generate multidimensional highway construction cost indexes (HCCIs) using two new concepts of i) dynamic item basket and ii) multidimensional HCCI, b) develop an enhanced framework for collection and utilization of digital Daily work Report (DWR) data, c) develop an automated methodology to generate as-built schedules using data collected from existing DWR systems, and d) analyze as-built schedules to develop a knowledge base of frequent precedence relationships of activities. The study achieves those objectives by utilizing three digital datasets: bid data, DWR data, and project characteristics data. Further, two standalone prototype systems, namely, Dyna-Mu-HCCI and ABSS are developed to automate computational methodologies for multidimensional HCCI calculation and as-built schedule development respectively. This study will aid SHAs to utilize currently unused datasets for informed budgeting and project control decisions. It demonstrates the importance of data analytics and visualization to obtain more value from the investment made in collecting construction data. Overall, this study serves as a step in making a transition from experience driven to data driven decision making in the construction industry

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures