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Acceptance and benchmark tests will provide important assurances that an automation system will meet defined performance requirements. Three acceptance tests should be required by a library and performed by the vendor: 1) a system reliability acceptance test, 2) one or more functional performance acceptance test, and 3) a full load response time acceptance test. Additionally, a library may require that benchmark tests be conducted after a vendor has been selected, but before a computer is installed in the library, if the vendor does not have installed systems comparable to the library's requirements, or if other similar systems have not previously met the library's performance objectives.

Although users of computerised production and inventory control systems may be aware of the possible occurrence of long periods of computer downtime, the authors believe that few companies are sufficiently prepared for such emergencies. This paper proposes guidance for drawing up contingency plans to ensure against this vulnerability.

In this article a case study is reported which deals with identifying the sources of downtime, and a procedure which could help management to predict whether the daily production standards in auto assembly‐line operations could be met given the intensity of sources of downtime. This study was conducted for a large auto engine manufacturer. The engine assembly line under study is subject to good preventive maintenance to avert unexpected breakdowns that would shut down the line or lower the quality so as to reduce the yield in total. Two multivariate statistical procedures are used – factor analysis and multiple discriminant analysis.

When it comes to availability, Web site operators should take a page from Yogi Berra's playbook. When asked whether he would be dining at a famous restaurant, the legendary Yankee catcher said, “Nobody goes there anymore. It's too crowded.” Likewise, if your Web site is too crowded with volume it can't handle, or suffers downtime for any reason, the “e” portion of your business is quickly closed.

Downtime is a process parameter that substantially impacts on the operating hours and results in production losses, thus motivating maintenance engineers to control process plants. Notwithstanding, the impacting nature of process equipment failure on the operating hours in bottling plants remains inadequately examined. In this paper, the cause-and-effect analysis was used to establish the root cause of the downtime problem and Pareto analysis employed to justify the greatest opportunities for improvement in reducing downtime and increasing reliability levels. Weibull analysis is then conducted on the industrial setting. Novel aspect ratios are proposed.

Using the Weibull failure function of machines as a principal facilitator to produce failure predictions, the downtime behaviour of a process plant was modelled and tested with practical data from a bottling process plant. This research was conducted in a Nigerian process bottling plant where historical data were examined.

The analysis of the results shows the following principal outcome: First, the machines with the highest and least downtime values are 2 and 5, respectively, with correspondingly mean values of 22.83 and 4.39 h monthly. Second, the total downtime 92.05 and 142.14 h for the observed and target downtime, with a coefficient of determination of 0.5848 was recorded. Third, as month 1 was taken as the base period (target), all the machines, except M5 had accepted performance, indicating proper preventive maintenance plan execution for the bottling process plant. Availability shows a direct relationship between the failure and uptime of the machines and the downtime impacts on production. Two machines had random failure pattern and five machines exhibited a wear-out failure pattern and probably due to old age and wear of components in the machines.

The major contribution of the paper is the Weibull modelling in a unique application to a bottling plant to avoid current practices that use reliability software that is not easily accessible.

Prediction of the duration of the downtime caused by maintenance, especially in the cases where the system considered consists of several repairable items, presents a challenge for maintenance managers, because of possible revenue losses during these intervals of time. Responds to this challenge through the new methodology for the fast, accurate prediction of maintainability measures related to the group replacement maintenance policy. It is applicable to group maintenance tasks in which individual replacement tasks are performed: simultaneously, sequentially, and combined. The method presented could be successfully used at the planning stage of the operations/production process when the information available is based on previous experience only, as well as at the stage when the process is performed. The applicability and usefulness of the methodology proposed is demonstrated through an illustrative numerical example.

Develops practical models for preventive maintenance policies using Bayesian methods of statistical inference. Considers the analysis of a delayed renewal process and a delayed alternating renewal process with exponential times to failure. This approach has the advantage of generating predictive distributions for numbers of failures and downtimes rather than relying on estimated renewal functions. Demonstrates the superiority of this approach in analysing situations with non‐linear cost functions, which arise in reality, by means of an example.

This is the third of a series of tabular presentations of data for operational computerised loans or circulation systems in specified countries. It follows the pattern established by the previous tabulations by grouping information about the systems covered under the series of descriptive headings that was developed as one of the first tasks of the then Circulation Working Party of the Aslib Computer Applications Group.

The current practice of maintenance on fishing vessels varies according to the operating policies of the owner/operator. On most occasions, the crew does not carry out regular maintenance while at sea. As such, all maintenance work is completed while the vessel is at the discharging port. The time between discharge ports can be as long as three to six months, which allows for failures on the machinery propagating and leading to a catastrophic breakdown. Discusses the possibility of avoiding such events by means of implementing an inspection regime based on the delay‐time concept. Operating and failure data that have been gathered from a fishing vessel are used to demonstrate the proposed approach. The outcome of the model is incorporated into the existing maintenance policy of the fishing vessel to assess its effectiveness.

Presents the experiences of a medium‐sized Australian manufacturer with cellular manufacturing over the past ten years. The case study reveals that careful planning and implementation are not the only component of ongoing success in a flexible cell environment and that effective management of inputs, layouts and human resources is required to ensure strategic benefits over a long period of time. Provides a summary of the initial planning and implementation of the flexible manufacturing cell (FMC), which was considered by management to be successful. The subsequent decisions taken by the company are then described, which resulted in the poor utilisation of the system. The recent actions taken by the manufacturing manager to enhance the performance of the FMC are then discussed. Concludes with a list of the lessons learned and the critical success factors in implementing and managing FMC.