Economic Control of Quality of Manufactured Product.

Perspectives in supply chain risk management

Normal accidents. Living with high-risk technologies

Researchers and practitioners alike have taken note of the potential value of an organization's IT infrastructure. IT infrastructure expenditures account for over 58 percent of an organization's IT budget and the percentage is growing at 11 percent a year. Some even have called IT infrastructure the new competitive weapon and see it as being crucial in developing a sustained competitive advantage. Unique characteristics of an IT infrastructure determine the value of that infrastructure to an organization. One characteristic, IT infrastructure flexibility, has captured the attention of researchers and practitioners. In fact, in most recent surveys featuring issues of most importance to IT executives, the development of a flexible and responsive IT infrastructure and related topics are always at or near the top of the responses. Although the importance of IT infrastructure flexibility has been established, the development of a valid, reliable instrument to measure this construct has not been reported in the literature. The purpose of this paper is to better define the IT infrastructure flexibility construct and to develop a valid, reliable measurement instrument for this construct. In addition to the definition and operationalization of the IT infrastructure flexibility construct, this study explores the instrument's predictive validity with possible antecedent and consequent variables.

Measuring the Flexibility of Information Technology Infrastructure: Exploratory Analysis of a Construct

In most real-world environments, scheduling is an ongoing reactive process where the presence of a variety of unexpected disruptions is usually inevitable, and continually forces reconsideration and revision of pre-established schedules. Many of the approaches developed to solve the problem of static scheduling are often impractical in real-world environments, and the near-optimal schedules with respect to the estimated data may become obsolete when they are released to the shop floor. This paper outlines the limitations of the static approaches to scheduling in the presence of real-time information and presents a number of issues that have come up in recent years on dynamic scheduling.

The paper defines the problem of dynamic scheduling and provides a review of the state-of-the-art of currently developing research on dynamic scheduling. The principles of several dynamic scheduling techniques, namely, heuristics, meta-heuristics, multi-agent systems, and other artificial intelligence techniques are described in detail, followed by a discussion and comparison of their potential.

/pdf/a-survey-of-dynamic-scheduling-in-manufacturing-systems-1u4bc63f51.pdf

A survey of dynamic scheduling in manufacturing systems

Scheduling of job shops has been extensively researched over the last three decades and it continues to attract the interests of both academic researchers and practitioners. This paper provides a state-of-the-art survey of the simulation-based research on dynamic job shop scheduling with a distinct emphasis on two important aspects. First, job-shop simulation modeling and experimental considerations are discussed with a review of the different approaches taken in the literature. Second, a review of the different studies is provided with a focus on their findings on the job shop performance criteria of interest. This paper is aimed at both practicing managers and researchers in the area of job shop scheduling because of the following considerations: 1. (i) The number of factors that characterize a job shop is very large and there is considerable variation in modeling and experimentation across the vast number of studies reported. Important research findings relevant to these issues reviewed in this paper would facilitate comparison of the currently available research results and their extension or application to other situations. 2. (ii) A review of the various studies focusing on some of the more important performance criteria should help practitioners in the selection of scheduling rules to match the criterion particularly relevant to their shops. 3. (iii) Recent studies which have modeled job shops as dual-resource constrained systems and assembly shops have been included in this survey for a more comprehensive coverage. A detailed bibliography is included and every effort has been made to make the survey up-to-date.

Dynamic job shop scheduling: A survey of simulation research

When supply lead times are uncertain, the simultaneous procurement from two sources offers savings in inventory holding and shortage costs. Economies are achieved if these savings outweigh the increase in ordering costs. In this paper we analyze dual sourcing in the context of the "reorder point, order quantity" inventory model with constant demand and stochastic lead times and compare it with single sourcing. Two cases are studied, using the uniform and the exponential distributions, which may be thought of as two extreme ways of representing stochastic lead times. In our two-vendor model, the order quantity is split equally between the two vendors and the split orders are placed simultaneously when the inventory position reaches the reorder level. A comparison of the total expected costs suggests that when the uncertainty in the lead times is high and the ordering costs are low, dual sourcing could be cost effective.

Sole Versus Dual Sourcing in Stochastic Lead-Time s, Q Inventory Models

Given the crucial role of process modeling in product development (PD) project management research and practice, and the variety of models proposed in the literature, a survey of the PD process modeling literature is timely and valuable. In this work, we focus on the activity network-based process models that support PD project management and present a comprehensive survey of the literature published in the last decade. To organize our survey, we use a framework based on the purposes of PD process models: project visualization, project planning, project control, and project development. For each purpose, we provide an overview of the relevant models, highlight their key assumptions and findings, synthesize key insights, and illuminate avenues for further research. Although the survey reveals many insights and opportunities, five major areas for future study became apparent: activity interactions, global process improvements, process models as an organizing structure for knowledge management, modeling in cases of uncertainty and ambiguity, and determining the optimum amount of process prescription and structure for an innovative project.

http://sbuweb.tcu.edu/tbrowning/Publications/Browning%20&%20Ramasesh%20(2007)--PD%20PM%20Lit%20Survey.pdf

Ranga V. Ramasesh

Papers

Dynamic job shop scheduling: A survey of simulation research

Sole Versus Dual Sourcing in Stochastic Lead-Time s, Q Inventory Models

A Survey of Activity Network‐Based Process Models for Managing Product Development Projects

A conceptual framework for tackling knowable unknown unknowns in project management

Measurement of manufacturing flexibility: A value based approach