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Deals with business parks in excess of 250,000 sq.ft., but claims the principles apply to smaller schemes. Establishes the need for management. Defines the objectives. Examines the responsibilities, tasks and strategy from the design stage onwards. Advocates an holistic approach, embracing design, marketing, investment, management and stakeholder care.

The purpose of the paper is to show that modern markets are characterized by rapidly changing environments and numerous external forces. Under these conditions, product lifetimes are rapidly reducing. Therefore, products require optimum inspection policies to maintain high quality and reduce costs in the competitive market. This study aims to establish optimal inspection policies of reliability analysis for quantal‐response product with Weibull lifetime components.

This study considers a product consisting of m different components in series with lifetimes that follow Weibull distributions, and applies a competing failure model to examine the proposed series system for quantal‐response products. The maximum likelihood estimators of parameters of the Weibull distribution are derived based on the quantal‐response data in the proposed series system. The statistical features of the model are illustrated through a numerical example of two‐component series products, and the properties of the maximum likelihood estimators were studied via Monte Carlo simulation under a two‐stage inspected scheme for various sampling sizes and inspection time conditions.

Simulation results demonstrate not only that the optimum inspection condition is the inspection times at T₁=0.2 and T₂=0.5 for the two‐stage inspected scheme, but also that the economical sampling size is 150 for both cases.

This research results can be applied to the analysis of one‐shot products, e.g. firework, ammunition, airbag, injector, with Weibull components lifetime distribution or the stockpile storage test.

In daily life, many products, such as light bulbs, fuses, dry batteries, fireworks, semiconductors, are non‐repairable. The non‐repairable products are usually referred to as one‐shot products, or as failed products that are not worth repairing. A one‐shot product is usually required to perform a function once only since its use is normally accompanied by an irreversible reaction or process, e.g. chemical reaction or physical destruction. However, most one‐shot products being stored or deployed are usually not under continuous surveillance. The failed products can only be found by inspection or at the beginning of operation. Therefore, this paper seeks to assess the reliability of one‐shot products.

The study considers a series system consisting of m components with lifetime following Weibull distribution, and applies a competing failure model to investigate the proposed series system for one‐shot products. The maximum likelihood estimators (MLEs) of parameters of the Weibull distribution based on the quantal‐response data in the proposed series system are derived. The model is illustrated with a two‐component series system, and the statistical properties of the MLEs are investigated by Monte Carlo simulation under the two‐stage inspection scheme and the three‐stage inspection scheme.

Simulation results reveal not only that the MLEs of Weibull parameters gradually approximate the true values of Weibull parameters under rising sample sizes, but also that the precision and accuracy of the MLEs of parameters increase with an increasing sample size. Furthermore, the standard deviations of MLEs of Weibull parameters for the two‐stage inspection scheme are smaller than those for the three‐stage inspection scheme.

The paper focuses on the reliability assessment of one‐shot products, e.g. firework, ammunition, airbag, injector, dry battery, with Weibull components lifetime distribution.

Most of the literature on the design of accelerated life test (ALT) plan focus on a single system (subsystem) totally disregarding its internal configuration. Many a times it is not possible to identify the components that cause the system failure or that the cause can only be identified by a subset of its components resulting in a masked observation. The purpose of this paper is to deal with the planning of ramp-stress accelerated life testing for a high-reliability parallel system comprising two dependent components using masked failure data. Such a testing may prove to be useful in a twin-engine aircraft. A ramp-stress results when stress applied on the system increases linearly with time.

A parallel system with two dependent components is taken with dependency modeled by Gumbel-Hougaard copula. The stress-life relationship is modeled using inverse power law, and cumulative exposure model is assumed to model the effect of changing stress. The method of maximum likelihood is used for estimating design parameters. The optimal plan consists in finding optimal stress rate using D-optimality criterion.

The optimal plan consists in finding optimal stress rate using D-optimality criterion by minimizing the reciprocal of the determinant of Fisher information matrix. The proposed plan has been explained using a numerical example and carrying out a sensitivity analysis.

The model formulated can help reliability engineers obtain reliability estimates quickly of high-reliability products that are likely to last for several years.

Examines Just‐in‐Time (JIT) from its evolution as a Japanese concept through to a review of its philosophy and implementation. Cites several techniques of implementation. Includes a review of the early work of various researchers and practitioners. Concludes that JIT is a very effective manufacturing philosophy which is universal in nature encompassing all aspects of manufacturing. Suggests a few deficiencies in current literature.

This chapter discusses the empirical data analysis that will form the basis of the early pricing framework. It focusses on the complexity of furniture production and describes the historical production data collected from companies, along with the potential applications of machine learning for knowledge management purposes. The chapter then presents the results of machine learning for early cost estimation as part of a lean innovation that is affordable and accessible for small and medium-sized enterprises (SMEs). Finally, the chapter describes an experiment on the structured expert evaluation methodology, which shows that a well-formed panel of experts can increase the predictive power of machine learning solutions, particularly at extreme points.

ALL who have visited Liverpool for any length of time have affection for her. She lies alongside a noble river, watched over by the lofty Liver building and the perhaps more architecturally perfect offices of the Mersey Dock authorities. Even in these days, when the very largest ships have been diverted to Southampton, splendid vessels come from and go to the ends of the earth almost daily. The river is the essential fact about Liverpool; she was born of the river and her waterfront is one of the world's rendezvous. As a city she compares favourably with any English town, and perhaps excels most in her few splendid buildings, amongst which the new and rapidly growing Cathedral takes first rank.

Recently, it has been recognized that production control systems for multi‐stage manufacturing processes can be classified into push‐type and pull‐type systems. The push‐type systems are commonly defined as those types of materials requirements planning system which utilize the forecast of demands. The pull‐type systems, on the other hand, are those where order quantities are determined on the basis of real demand. Describes a hybrid push/pull production control system, operated periodically, which combines the benefits of both systems. Discusses theoretical arguments in support of this system and numerical studies are shown to give insight into the system′s performance. Hybrid push/pull‐type systems can attain a higher degree of effectiveness if they are appropriately operated.

It is often assumed that prison staff are particularly stressed due to their frequent exposure to traumatic events, which may damage not only individuals but also prisons and prisoners. While the impact of such stress may be recognised, the factors contributing to its development are unclear.The work reported here is part of a larger investigation of health care provision in a Greater London prison. Qualitative approaches were used to access the understandings of staff and key informants of the difficulties associated with their working environment. This enabled us to accommodate different working contexts, ensuring that the findings were grounded in the reality of the work undertaken by the participants.The data revealed that lack of training contributed significantly to the development of stress, reducing confidence in dealing with the many traumatic situations encountered. However, interpersonal relationships provided mutual support during crises. General working conditions, including workload and staff redeployment, were also important contributors to high levels of sickness‐absence which, in turn, exacerbated stress. Poor management practices, combined with a perceived lack of support, further aggravated stress.While it may be tempting to blame individuals for their inability to cope, all organisations have a duty of care to their employees and must take steps, at both the individual and organisational level, to prevent and manage work‐related stress.