Knowledge extraction for production management

A procedure and underlying algorithm for extracting knowledge from production and inventory databases to support engineering management activities is described. The process searches for, detects and isolates behaviour patterns inherent in the data. It relates these patterns to production irregularities, suggests connections with specific causes and helps propose possible corrective or preventive actions. The approach is based on a four-phase procedure: (1) the decision-maker focuses on the subject or difficulty at issue, represented by a target concept; (2) the KEDB algorithm, based on a machine learning approach, processes the relevant database and provides knowledge characterizing and classifying the target concept; (3) the output is interpreted in Pareto fashion as a series of possible circumstances explaining the target concept behaviour; and (4) based on these causes, the decision-maker decides on possible corrective actions to improve the situation, or preventive actions to forestall unfavourable conditions. A case study based on an actual quality control database is detailed.     

Discrete-time complementary models and smoothing

The fact that the smoothing error is a (wide sense) Markov process is somehow surprising since smoothed estimates depend upon both past and future data. In this paper we first give a simple and general proof of this fact. Then we use the so-called complementary models introduced by Weinert and Desai to derive forwards and backwards markovian models for the smoothing error in state-space models. By exploring the structure of the complementary models we show that, under certain restrictions, only two simple structured models exist, one that runs forwards in time and the other that runs backwards in time. The forwards complementary model leads to the forward Rauch-Tung-Striebel (RTS) smoothing formula and to a backwards markovian model for the error, whereas the backwards model leads to the backward RTS formula and to a forwards error model. The two models for the smoothing error can be derived one from the other by a forward-backward transformation that preserves the sample paths. Finally, by using a combination of the two complementary models we give yet another proof for the two-filter smoothing formula.     

Design and nonlinear servo control of MEMS mirrors and their performance in a large port-count optical switch

In this paper, we demonstrate full closed-loop control of electrostatically actuated double-gimbaled MEMS mirrors and use them in an optical cross-connect. We show switching times of less than 10 ms and optical power stability of better than 0.2 dB. The mirrors, made from 10-/spl mu/m-thick single-crystal silicon and with a radius of 400-450 /spl mu/m, are able to tilt to 8/spl deg/ corresponding to 80% of touchdown angle. This is achieved using a nonlinear closed-loop control algorithm, which also results in a maximum actuation voltage of 85 V, and a pointing accuracy of less than 150 /spl mu/rad. This paper will describe the MEMS mirror and actuator design, modeling, servo design, and measurement results.     

Crankback Prediction in Hierarchical ATM Networks

When an ATM node discovers that it cannot continue the setup of a virtual channel under the requested Quality of Service (QoS), it initiates a backtracking procedure called crankback. We propose a novel scheme, referred to as crankback prediction, that decreases the crankback overhead. Under the proposed scheme, nodes check during the connection admission control procedure whether the establishment of a virtual channel has a good chance to be admitted over the entire designated route. If this is not the case, crankback is initiated even before a particular QoS parameter is violated. The main idea behind the proposed scheme is to allocate a quota to the Peer Groups (PGs) along the message path, and then to suballocate this quota to the child PGs of these PGs. This process continues recursively until reaching the 1-level PG, which contains only physical nodes. The main advantage of the proposed scheme is that it lowers the setup delay and the processing and communication load imposed by signaling messages that establish unused portions of Virtual Channels (VCs)     

A Study of Lot Sizing Algorithms

The many MRP lot-sizing algorithms proposed imply four underlying time-phasing requirements: minimizing inventory, maintaining uniform batch sizes, maintaining regular order cycles, and attaining minimum costs. This study examines the cost behavior of four exact and two classical algorithms addressing these structures. Several parameters, describing the demand profile, planning horizon and component costs enable effective evaluation and prediction of cost behaviour. The study shows that: (1) imposing regularity constraints on an MRP schedule leads to costs 14% above the minimum for fixed batch sizing, and 2% for regular order cycling; (2) fixed order cycle schedules show costs close to the minimum attainable, thus supporting the use of this approach in practice; (3) the classical POQ schedules also show good cost performance (11% above minimum); and (4) the cost behaviour of a wide range of MRP demand profiles and cost components can be fairly well predicted (to 7% on the average) using simplified “ideal” relationships.     

The olive compound 4-hydroxytyrosol inactivates Staphylococcus aureus bacteria and Staphylococcal Enterotoxin A (SEA)

The foodborne pathogen Staphylococcus aureus produces the virulent staphylococcal enterotoxin A (SEA), a single chain protein which consists of 233 amino acid residues with a molecular weight of 27078 Da. SEA is a superantigen that is reported to contribute to animal (mastitis) and human (emesis, diarrhea, atopic dermatitis, arthritis, and toxic shock) syndromes. Changes in the native structural integrity may inactivate the toxin by preventing molecular interaction with cell membrane receptor sites of their host cells. In the present study, we evaluated the ability of the pure olive compound 4-hydroxytyrosol and a commercial olive powder called Hidrox-12, prepared by freeze-drying olive juice, to inhibit S. aureus bacteria and SEA's biological activity. Dilutions of both test substances inactivated the pathogens. Two independent cell assays (BrdU incorporation into newly synthesized DNA and glycyl-phenylalanyl-aminofluorocoumarin proteolysis) demonstrated that the olive compound 4-hydroxytyrosol also inactivated the biological activity of SEA at concentrations that were not toxic to the spleen cells. However, efforts to determine inhibition of the toxin by Hidrox-12 were not successful because the olive powder was cytotoxic to the spleen cells at concentrations found to be effective against the bacteria. The results suggest that food-compatible and safe antitoxin olive compounds can be used to inactivate both pathogens and toxins produced by the pathogens. Practical Application: The results of this study suggest that food-compatible and safe antitoxin olive compounds can be used to reduce both pathogens and toxins produced by the pathogens in foods.     

Exploring the Effects of Glycosylation and Etherification of the Side Chains of the Anticancer Drug Mitoxantrone

Herein we report the synthesis and biological evaluation of symmetric and asymmetric analogues of the DNA intercalating drug mitoxantrone (MTX) in which the side chains of the parent drug were modified through glycosylation or methyl etherification. Several analogues with glycosylated side chains exhibited higher DNA affinity than the parent MTX. The most potent in vitro cytotoxicity was observed for MTX analogue 8 (1,4‐dimethoxy‐5,8‐bis[2‐(2‐methoxyethylamino)ethylamino]anthracene‐9,10‐dione) with methoxy ether containing side chains. Treatment of melanoma‐bearing mice with MTX or analogue 8 decreased the intraperitoneal tumor burden relative to untreated mice; the effect of 8 was less pronounced than that of MTX. In vitro metabolism assays of MTX with rabbit liver S9 fraction gave rise to several metabolites; almost no metabolites were detected for MTX analogue 8 . The results presented indicate that derivatization of the MTX side chain primary hydroxy groups may result in a significant improvement in DNA affinity and lower susceptibility to the formation of potentially toxic metabolites.     

A simulation model for risk analysis of toxic chemical storage

With the increasing complexity of chemical plants and the growing public concern for the safe manufacture, transport, and disposal of these chemicals, there exist a need to assist decision-makers in project evaluation with regard to risk.

Extensive work has been done in risk analysis area related to nuclear industry. The amount of research and applications of risk analysis methodology in chemical industry is seriously lacking. Direct application of some of the risk analysis techniques used for nuclear risk studies is not always appropriate to the chemical industry.

The use of simulation models to overcome some of the problems of direct application of probabilistic risk assessment (PRA) methodologies is evaluated in this paper. A simulation model is developed for a toxic chemical storage risk analysis problem. The results of the simulation model are compared to the results of using standard fault tree methodology.