Quantifying the costs and benefits of product variety on key performance measures-a simulation study.

In today\u27s market customers are increasingly demanding a greater number of options in the products they purchase. Offering products in greater variety helps industries cater to a wider range of customers. However, at the same time, this product proliferation is creating new problems for manufacturers. The effect of an increase in the variants of a product on the supply chain and production operations is largely unknown. Understanding this affect along with the benefits of increased product variety on the company\u27s market share would greatly assist industries in making a return on investment analysis. In this thesis, we develop a simulation model of the production operations of a typical manufacturing company, and study the effect of changing product variety on these operations. This is done by determining the variation in the key performance indicators (KPIs) such as product cycle time, work-in-process (WIP) and resource utilization when changes are made to the variety of the products manufactured. This thesis consists of three simulation models representing three different scenarios in a manufacturing environment. The models built using the simulation software-ARENA, compare the three production strategies employed to cater to the current variety and when new variety is added to the current mix. The first model represents the current manufacturing design. The model parameters and outputs were compared with the real manufacturing setting to make sure it is consistent. The second model represents a scenario where changes and additions are made to the initial design, to meet the production requirements of the new product mix. No changes are made to accommodate the takt time requirements of the customer. In the third simulation model design changes are made so as to meet takt time requirements and thus satisfy the required throughput rules. The three models are then compared to see which one performs the best in terms of meeting customer requirements and KPIs. Based on the results we believe that changing product variety can have a significant impact on an industry\u27s manufacturing operations and significant investments might be required to mitigate these effects

Symbiotic approaches to work and technology

Production Planning;production

Evaluation and synthesis of methods for measuring system engineering efficacy with a project and organization

Thesis (S.M.)--Massachusetts Institute of Technology, System Design and Management Program, 2007.Includes bibliographical references (p. [126]-128).The need for robust systems engineering in product development has been understood by those developing product in the aerospace and defense industries since the days of the Atlas ballistic missile program. In recent times industries developing systems of similar complexity have come to respect the value of systems engineering. Systems engineering is the glue which binds a large technical team and focuses the engineering effort towards satisfying a set of realizable customer needs. EIA/IS-632 definition of systems engineering is as follows; "Systems engineering is an interdisciplinary approach encompassing the entire technical effort to evolve and verify an integrated and life-cycle balanced set of system people, product and process solutions that satisfy customer needs."To control and improve a process a viable set of measures must be in place. Existing measures of the strength of the systems engineering process in a specific project address only project execution (e.g. earned value) and technical performance. When applied properly these metrics provide valuable insight into the status (cost and schedule) of a project and a products ability to meet customer needs. However, few of these existing measures are progressive in nature and as such fail to provide early warnings of systems engineering process failure. What are needed are prognostics for the systems engineering effort; gauges to provide predictions of future events which impact product cost, schedule and/or performance. The Lean Aerospace Initiative (LAI), working with the International Council on Systems Engineering (INCOSE), released a guide (in Beta form) in December of 2005 outlining a progressive set of thirteen leading indicators to address this need. This set of metrics has yet to be been verified against an active or historical project but provides a starting ground for additional research.by Timothy Daniel Flynn.S.M

National Wind Tunnel Complex (NWTC)

The National Wind Tunnel Complex (NWTC) Final Report summarizes the work carried out by a unique Government/Industry partnership during the period of June 1994 through May 1996. The objective of this partnership was to plan, design, build and activate 'world class' wind tunnel facilities for the development of future-generation commercial and military aircraft. The basis of this effort was a set of performance goals defined by the National Facilities Study (NFS) Task Group on Aeronautical Research and Development Facilities which established two critical measures of improved wind tunnel performance; namely, higher Reynolds number capability and greater productivity. Initial activities focused upon two high-performance tunnels (low-speed and transonic). This effort was later descoped to a single multipurpose tunnel. Beginning in June 1994, the NWTC Project Office defined specific performance requirements, planned site evaluation activities, performed a series of technical/cost trade studies, and completed preliminary engineering to support a proposed conceptual design. Due to budget uncertainties within the Federal government, the NWTC project office was directed to conduct an orderly closure following the Systems Design Review in March 1996. This report provides a top-level status of the project at that time. Additional details of all work performed have been archived and are available for future reference

Systems Engineering Leading Indicators Guide, Version 2.0

The Systems Engineering Leading Indicators Guide editorial team is pleased to announce the release of Version 2.0. Version 2.0 supersedes Version 1.0, which was released in July 2007 and was the result of a project initiated by the Lean Advancement Initiative (LAI) at MIT in cooperation with: the International Council on Systems Engineering (INCOSE), Practical Software and Systems Measurement (PSM), and the Systems Engineering Advancement Research Initiative (SEAri) at MIT. A leading indicator is a measure for evaluating the effectiveness of how a specific project activity is likely to affect system performance objectives. A leading indicator may be an individual measure or a collection of measures and associated analysis that is predictive of future systems engineering performance. Systems engineering performance itself could be an indicator of future project execution and system performance. Leading indicators aid leadership in delivering value to customers and end users and help identify interventions and actions to avoid rework and wasted effort. Conventional measures provide status and historical information. Leading indicators use an approach that draws on trend information to allow for predictive analysis. By analyzing trends, predictions can be forecast on the outcomes of certain activities. Trends are analyzed for insight into both the entity being measured and potential impacts to other entities. This provides leaders with the data they need to make informed decisions and where necessary, take preventative or corrective action during the program in a proactive manner. Version 2.0 guide adds five new leading indicators to the previous 13 for a new total of 18 indicators. The guide addresses feedback from users of the previous version of the guide, as well as lessons learned from implementation and industry workshops. The document format has been improved for usability, and several new appendices provide application information and techniques for determining correlations of indicators. Tailoring of the guide for effective use is encouraged. Additional collaborating organizations involved in Version 2.0 include the Naval Air Systems Command (NAVAIR), US Department of Defense Systems Engineering Research Center (SERC), and National Defense Industrial Association (NDIA) Systems Engineering Division (SED). Many leading measurement and systems engineering experts from government, industry, and academia volunteered their time to work on this initiative

NASA Systems Engineering Handbook

This handbook is intended to provide general guidance and information on systems engineering that will be useful to the NASA community. It provides a generic description of Systems Engineering (SE) as it should be applied throughout NASA. A goal of the handbook is to increase awareness and consistency across the Agency and advance the practice of SE. This handbook provides perspectives relevant to NASA and data particular to NASA. The coverage in this handbook is limited to general concepts and generic descriptions of processes, tools, and techniques. It provides information on systems engineering best practices and pitfalls to avoid. There are many Center-specific handbooks and directives as well as textbooks that can be consulted for in-depth tutorials. This handbook describes systems engineering as it should be applied to the development and implementation of large and small NASA programs and projects. NASA has defined different life cycles that specifically address the major project categories, or product lines, which are: Flight Systems and Ground Support (FS&GS), Research and Technology (R&T), Construction of Facilities (CoF), and Environmental Compliance and Restoration (ECR). The technical content of the handbook provides systems engineering best practices that should be incorporated into all NASA product lines. (Check the NASA On-Line Directives Information System (NODIS) electronic document library for applicable NASA directives on topics such as product lines.) For simplicity this handbook uses the FS&GS product line as an example. The specifics of FS&GS can be seen in the description of the life cycle and the details of the milestone reviews. Each product line will vary in these two areas; therefore, the reader should refer to the applicable NASA procedural requirements for the specific requirements for their life cycle and reviews. The engineering of NASA systems requires a systematic and disciplined set of processes that are applied recursively and iteratively for the design, development, operation, maintenance, and closeout of systems throughout the life cycle of the programs and projects

Expanded Guidance for NASA Systems Engineering. Volume 1: Systems Engineering Practices

This document is intended to provide general guidance and information on systems engineering that will be useful to the NASA community. It provides a generic description of Systems Engineering (SE) as it should be applied throughout NASA. A goal of the expanded guidance is to increase awareness and consistency across the Agency and advance the practice of SE. This guidance provides perspectives relevant to NASA and data particular to NASA. This expanded guidance should be used as a companion for implementing NPR 7123.1, Systems Engineering Processes and Requirements, the Rev 2 version of SP-6105, and the Center-specific handbooks and directives developed for implementing systems engineering at NASA. It provides a companion reference book for the various systems engineering-related training being offered under NASA's auspices