Reducing cycle times in manufacturing and supply chains by input and service rate smoothing

A key performance parameter of a manufacturing network or supply chain is its cycle time; the time that a typical item spends in the network. A previous simulation study on a semiconductor assembly and test facility showed that cycle times could be reduced by having smooth input and service rates. This suggested that there is a “cycle time principle” that, for a system with a specified throughput or input rate, the shortest cycle times are obtained when the input and service rates do not vary over time. We prove that this principle is true for the M/G/1 and M/M/s queueing systems and Jackson networks. The analysis involves establishing several results on the concavity of waiting time probabilities and the convexity of expected waiting times and queue lengths, as functions of input and service rates. These results also have natural uses in other optimization problems.     

Evaluating the impact of CASE: an empirical comparison of retrospective and cross-sectional survey approaches

The purpose of this paper is to evaluate two methods of assessing the productivity and quality impact of Computer Aided Software Engineering (CASE) and Fourth Generation Language (4GL) technologies: (1) by the retrospective method; and (2) the cross-sectional method. Both methods involve the use of questionnaire surveys. Developers' perceptions depend on the context in which they are expressed and this includes expectations about the effectiveness of a given software product. Consequently, it is generally not reliable to base inferences about the relative merits of CASE and 4GLs on a cross-sectional comparison of two separate samples of users. The retrospective method that requires each respondent to directly compare different products is shown to be more reliable. However, there may be scope to employ cross-sectional comparisons of the findings from different samples where both sets of respondents use the same reference point for their judgements, and where numerical rather than verbal rating scales are used to measure perceptions.     

Effect of Freezer Programs on Real-Time Storage Results of Dissolution Profiles

Carstensen and Rhodes¹ have suggested that when, in stability programs, assays cannot be performed immediately after the protocol-designated storage time, then freezing them until such a time when assays can be performed would be a reasonable manner to retain the protocol schedule. They caution, however, that such a procedure may not be valid for dissolution data. The article to follow deals with real-time data showing that such a process is feasible for Nalidixic Acid tablets (and presumably for other tablets as well), and that, furthermore, the dissolution pattern would seem to be “frozen” as well.     

The effects of pressure on the isothermal fluid behavior of bituminous coals

An investigation into the effects of pressure (helium gas) on the isothermal fluid behavior includes: (1) the effect of pressure on the rate of melting and coking as evidenced by the rate constants k(melt) and k(coke); (2) the effect of pressure on the energies of activation of melting and coking; (3) the effects of pressure on the characteristic times; (4) the effects of pressure on the maximum isothermal fluidity. Results from the effects of pressure on k(melt) revealed that it was generally the high total sulfur, low nitrogen, low reactives/mineral matter ratio, medium rank coals which show the greatest increase in k(melt), whereas the highest rank coals show the least decrease in k(coke). The energies of activation of melting and coking were not significantly affected by pressure. The investigation also reveals increases or decreases in the respective times of softening, maximum fluidity, resolidification and total time of fluid behavior under isothermal pressurized conditions. There appears the possibility that these shifts may be rank dependent. Additionally, the lower rank coals show the largest relative increase in their fluidities when subjected to pressure. Empirical relationships were derived in order to quantitatively predict the maximum isothermal fluidity for most (fluid) coals at a given pressure.     

The organisational learning effects of management accounting information under advanced manufacturing technology

This study empirically examined the organisational learning effects of the nonfinancial performance information provided by management accounting information systems (MAISs) under advanced manufacturing technology (AMT). In this study, a target costing system and the frequent and quick reporting of information were considered the facilitators of learning. First, we examined the relationships between AMT level and the amount of nonfinancial performance information produced by MAISs. The empirical results showed that there are significant positive relationships between the level of AMT and nonfinancial performance information. With a systems approach, we also proved the impact of the relationships among AMT levels, nonfinancial performance information and learning facilitators on the organisational performance of a firm. The results of our research suggest that under a high level of AMT, for the provision of information to result in an increase of performance through organisational learning, a target costing system must be introduced and a large amount of information should be provided frequently and quickly. The results of this study also showed that although AMT level may be low, fairly well-arranged facilitators and a moderately large amount of information may be necessary for the improvement of performance. In conclusion, effective organisational learning depends on the provision of relevant information as well as efficient learning support mechanisms.     

A distributed adverse drug reaction detection system using intelligent agents with a fuzzy recognition‐primed decision model

Discovering unknown adverse drug reactions (ADRs) in postmarketing surveillance as early as possible is highly desirable. Nevertheless, current postmarketing surveillance methods largely rely on spontaneous reports that suffer from serious underreporting, latency, and inconsistent reporting. Thus these methods are not ideal for rapidly identifying rare ADRs. The multiagent systems paradigm is an emerging and effective approach to tackling distributed problems, especially when data sources and knowledge are geographically located in different places and coordination and collaboration are necessary for decision making. In this article, we propose an active, multiagent framework for early detection of ADRs by utilizing electronic patient data distributed across many different sources and locations. In this framework, intelligent agents assist a team of experts based on the well‐known human decision‐making model called Recognition‐Primed Decision (RPD). We generalize the RPD model to a fuzzy RPD model and utilize fuzzy logic technology to not only represent, interpret, and compute imprecise and subjective cues that are commonly encountered in the ADR problem but also to retrieve prior experiences by evaluating the extent of matching between the current situation and a past experience. We describe our preliminary multiagent system design and illustrate its potential benefits for assisting expert teams in early detection of previously unknown ADRs. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 827–845, 2007.