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We present two contingency rules to control a production process subject to a single assignable cause, i.e. the process shifts from in‐control to out‐of‐control state when the single assignable cause occurs. In this paper, we assume a 100 per cent inspection policy as opposed to the sampling concept. However, the first rule we suggest is comparable with the traditional sampling model in that its criterion to intervene in the process is based on the number of defective products. The second rule uses more information than the first does: it triggers intervening in the process when the inter‐arrival time between two consecutive defective products is smaller than an optimally derived cut‐off rate. We first show how the two rules can be derived, and, as a preliminary analysis, propose conditions under which one contingency rule might be more effective than the other.

Many of the traditional controls that accountants and auditors are most familiar with can be traced to bureaucratic management. This article introduces a business process control model that fully captures the broader array of process controls now being implemented by world‐class organizations, including value‐adding controls focused on quality, cost and time. The article describes the categories of controls included in the model, presents a new way of mapping process controls that reflects the model, and illustrates the use of the model within the context of an actual business process. The article also discusses the primary benefits of adopting the model. First, the model provides a common business process control language and structure which will facilitate communications and foster a uniform understanding of process controls among senior executives, process owners, accountants and auditors. Second, the model provides a framework for comprehensively assessing business process risks and evaluating and improving business process controls.

Business processes have an open and dynamic character and are influenced by internal an external disturbances. Without an adequate use of feedback mechanisms, those processes become unstable and do not achieve the expected performance. The purpose of this paper is to face the challenge and to ensure a competitive quality level, a framework for entrepreneurial quality management is given.

Using the method of analogy formation the transfer of cybernetic approaches to business processes is shown. Especially quality control loops are analysed in order to find appropriate solutions for their design and implementation in enterprises.

As a core element of the paper an approach for the systematic implementation of control loops is given. This approach offers a framework and a description for an operative implementation of quality control loops for stable business processes.

The idea to use closed quality control loops for the design of several processes is already known. Anyway, both a robust framework and a appropriate, sufficient and detailed description for an operative implementation is the new aspect and an important further development within the topic.

Proposes the use of a β, or difference‐from‐nominal, control chart for short‐run industrial processes providing certain conditions are met. While some manufacturers have used delta charts in the past, only recently have delta charts been discussed in the literature –and then under a variety of different names. This has led to a situation where β charts have been inappropriately applied because the conditions for their use were not clearly understood. Explains the β control chart and the conditions appropriate for its use. In addition, presents a case study of the use of the β chart in a short‐run manufacturing process.

The implementation and use of statistical process control in a chemicals and plastics firm are examined. The essential external factors are focused upon, which are associated with the practical implementation of statistical process control. The important components of a Statistical Process Control process optimisation study are discussed in the context of their achievements at a manufacturing facility. Benefits achieved from a successful implementation of statistical process control are also discussed.

An economic adjustment model of a process whose quality can be affected by multiple special causes, resulting in changes of the process mean by incorrect adjustment of the process when it is operating according to its capability. A statistically constrained adjustment model is developed for the economic statistical design of X¯ control chart to control the process mean affected by multiple special causes. The objective is to determine the design parameters of the X¯ control chart, which minimize the total quality control cost. A Markov chain approach is used to derive the model. It is demonstrated that the expressions for the expected cycle time and the expected cycle cost with multiple special causes are easier to obtain by the proposed approach than by extending or adopting that in Collani et al. Application of the model is demonstrated through a numerical example.

Manufacturing industries are in the midst of a new technological revolution, characterised by the increasing advances and application of information and communication technology for both information processing and automatic control. A unique manufacturing methodology for non‐destructive, real‐time process optimization and quality certification has been developed. This includes the design of a decision support system (DSS) for controlling the optimized process. The DSS comprises the capability of supporting both the process operator and manager in the decision‐making process, allowing them to take advantage of the degrees of freedom of the physical system to make it work in a way where the optimized process control variables are under statistical control, resulting in optimized output factors that, in turn, secure higher productivity and improved quality.

An article in the Volume 13, Number 2 issue of the Managerial Auditing Journal introduced a comprehensive business process control model that captures the full spectrum of process controls being implemented by world‐class organizations, including value‐adding controls focused on quality, cost and time. The purpose of this article is to demonstrate a new approach to flowcharting business processes which highlights the five broad categories of controls included in the model. This approach clearly shows how the various types of controls interact with process activities and provides a basis for evaluating how effectively these controls contribute to the achievement of business process objectives.

This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.