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Presents an analytic framework for processing planning in industries where fixed batch sizes are common. The overall optimum processing plan is shown to be located on an envelope between the optimum JIT plan and the optimum level plan. These concepts provide the framework for understanding the overall optimum plan, and the framework leads to an efficient heuristic. The approach is practical, illustrated by a case study from the food industry, which shows the place of overall optimum planning within the company’s planning system and its implications for company performance.

The paper discusses the assignment of security clearances to employees in a security conscious organisation. New approaches are suggested for solving two major problems. First, full implementation of the “need‐to‐know” principle is provided by the introduction of data access statements (DAS) as part of an employee’s job description. Second, for the problem of setting up border points between different security clearances, the paper introduces a fuzzy set model. This model helps to solve this problem, effectively connecting it with the cost of security.

The paper discusses a set of models which can assist in developing security profiles of objects and subjects operating within industrial or commercial organisations’ databases. In these databases the information objects are often related to each other, having a hierarchical or even a network structure. A set of objects may be allowed to calculate other objects of a database. Security clearance must incorporate such possibilities.

Addresses the problem of implementing just‐in‐time (JIT) principles in a processing shop organized in a batch manufacturing environment. The focus is on a processing shop separated from an assembly shop by a parts store. Presents a multi‐criteria variant of the capacitated lot‐sizing model. The approach involves a pre‐emptive priority for JIT processing schedules, and a secondary priority for desirable load profiles. Solution properties are derived and used to facilitate the solution process for both the primary and secondary criterion models. Load profiles are assessed in the context of capacity requirements planning as well as from the alternative viewpoint of providing feedback to capacity planning through a consideration of capacity cushions. At both planning levels the approach is shown to allow optimum resource utilization without violating JIT principles. Presents optimization procedures, including a heuristic with an analytic performance bound.

In the present era of intense competition, industries are adopting lean manufacturing for successful survival. The concept of lean manufacturing is new for Indian process industries. The purpose of this paper is to investigate the status of lean manufacturing in Indian process industries in terms of lean practices, reasons and challenges of implementing lean manufacturing.

A survey was carried out to assess the level of lean implementation in Indian process industries. Statistical tests were conducted to assess the significant lean practices, reasons and challenges of implementing lean in Indian process industries.

It is observed that the level of implementation of lean manufacturing in Indian process industries is still low. Results indicate that Indian process industries those who have implemented lean found lean to be very useful to reduce wastes and to increase quality. Major lean practices being implemented by Indian process industries are primarily those which are related to waste elimination or improvement in quality. Indian process industries found that important challenges to implement lean are to produce in small batches, to arrange for lean experts and to impart training to employees.

In the present study, the sample size is small and hence, the findings should be generalized cautiously. Although the study indicates that lean can be very useful if implemented in Indian process industries but further empirical studies are required to quantify performance improvements through adoption of lean.

The paper explores status of lean adoption in Indian process industries. Considering the unique characteristics of process industries, the present research would be helpful for making strategies to implement lean in process industry setups.

This study seeks to explore the role of process orientation (PO) in organizations that go through a transition in implementing enterprise systems (ESs).

Based on an empirical survey of 3,000 large Canadian and US firms, this study investigates the role of PO in various aspects of ES implementation. Exploratory factor analysis is conducted using SPSS software to identify indicators and factors of measuring PO and various aspects of ES implementation. Furthermore, the LISREL software was used to perform the path analysis to identify the role of PO.

The results of the analysis strongly suggest that the PO levels at three phases of ES implementation are independent and, hence, require separate measurement. In addition, two research models are employed to examine 14 hypotheses associated with the role of PO in ES implementation. The findings indicate that process‐oriented organizations in our sample are more successful in ES implementation and have faced fewer challenges in the transition process.

This study unveils the role of PO in successful ES implementation. The champions of transition pay special attention to PO throughout the ES implementation. The findings reveal that under certain conditions PO can hinder or support the ES implementation in organizations.

This is the first study that measures PO at three phases of ES implementation. Moreover, two research models are employed to study the research topic, namely: preliminary model, and expanded model. Measurement of PO at three stages of transition provides a unique perspective to evaluate the effect of PO in organizations.

The success of business process re‐engineering (BPR) is dependent on the use of data‐driven methods that provide cost‐effective and optimal solutions. Today's business managers are inundated with methodologies and tools that claim to provide sustaining process improvement results. Determining the appropriate BPR method(s) to employ is a daunting task for many businesses. Understanding the technical complexities of these methods is even more overwhelming. However, with the increased availability of management science software, business managers can easily identify and employ proven management science techniques. Readily available software that provides timely results, is easily adaptable to resource changes, and does not require extensive technical competencies. This paper demonstrates how scientific management techniques, coupled with management science software (Management Scientist, Project Management and Excel), provided a feasible and achievable solution to a laboratory courier service BPR project. The solution yields a 19.5 percent reduction in annual laboratory courier specimen costs while improving service levels.

This paper sets out to present a reappraisal on advanced planning and scheduling (APS) systems in industrial settings and propose an effective approach for APS implementation.

A case study approach is adopted, and a research framework comprising human‐, technological‐, and organizational‐dimensions is developed to analyze the evidence database which includes business flows, system design documents, archival records, post‐system assessment, participant‐observation and semi‐structured interviews.

The findings indicate that real‐world production planning problems are ill‐defined, complex and dynamic. A post‐implementation evaluation reveals major pitfalls in the technology‐dominant approach, whose negative ramifications are usually overlooked. Besides, these APS implementation pitfalls are found to be attributable to the real‐world context, human factors and organizational aspects.

Despite advances in information technology (IT) and computer modeling techniques, humans still play critical roles in the production‐planning processes – especially in a complex and dynamic manufacturing environment where incomplete, ambiguous, inconsistent and untimely data make automatic planning unrealistic. A rational human‐computer collaboration scheme under an effective organizational structure would be in a better position to take advantage of the IT.

This paper presents a humans‐technology‐organization‐framework of real planning systems, which is employed to analyze a case of APS implementation. Practical insights are extracted as a result of this field research, and a realist approach is proposed to cope with the problems and pitfalls of APS implementation in industrial settings.

Reviews some new trends in parallel machine scheduling (PMS). PMS, as an area of research, is governed by questions that arise in production planning, flexible manufacture systems, computer control, etc. The main characteristic of these problems is to optimize an objective, with jobs to be finished on a series of machines with the same function. Gives a short review of new developments in PMS associated with the problems of just‐in‐time (JIT) production, pre‐emption with set‐up, and capacitated machine scheduling. Discusses non‐regular objectives oriented by the JIT concept; pre‐emption with set‐up; capacitated machine scheduling; and relationships between PMS and vehicle routeing problems.

The need effectively to integrate decision making tasks together with knowledge representation and inference procedures has caused recent research efforts towards the integration of decision support systems with knowledge‐based techniques. Explores the potential benefits of such integration in the area of business forecasting. Describes the forecasting process and identifies its main functional elements. Some of these elements provide the requirements for an intelligent forecasting support system. Describes the architecture and the implementation of such a system, the theta intelligent forecasting information system (TIFIS) that that first‐named author had developed during his dissertation. In TIFIS, besides the traditional components of a decision‐support onformation system, four constituents are included that try to model the expertise required. The information system adopts an object‐oriented approach to forecasting and exploits the forecasting engine of the theta model integrated with automated rule based adjustments and judgmental adjustments. Tests the forecasting accuracy of the information system on the M3‐competition monthly data.