Browsing by Author "Taylor, Robert E."
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- Application of DMAIC to integrate Lean Manufacturing and Six SigmaStephen, Philip (Virginia Tech, 2004-06-11)The slow rate of corporate improvement is not due to lack of knowledge of six sigma or lean. Rather, the fault lies in making the transition from theory to implementation. Managers need a step-by-step, unambiguous roadmap of improvement that leads to predictable results. This roadmap provides the self-confidence, punch, and power necessary for action and is the principal subject of this research. Unique to this research is the way the integration of lean and six sigma is achieved; by way of an integration matrix formed by lean implementation protocols and six sigma project phases. This integration matrix is made more prescriptive by an integrated leanness assessment tool, which will guide the user given their existing level of implementation and integration. Further guidance in each of the cells formed by the integration matrix is provided by way of phase methodologies and statistical/non-statistical tools. The output of this research is a software tool that could be used in facilities at any stage of lean implementation, including facilities with no existing lean implementation. The developed software tool has the capability to communicate among current and former project teams within any group, division, or facility in the organization. The developed software tool has also the capability to do data analysis (Example: Design of Experiments, Value Stream Mapping, Multi-Vari Analysis etc.). By way of the integration matrix, leanness assessment and the data analysis capability, the developed software tool will give managers a powerful tool that will help in their quest to achieve lean six sigma.
- The effect of scheduling on air traffic delayCrockett, Randal R. (Virginia Tech, 1974-05-05)At the present time, millions of dollars are being lost by major airlines each year because of the inability of high density air terminals to efficiently service all of the demands placed upon them during peak periods of demand. Up to the present time, studies involving congestion have been aimed primarily at the implementation of computerized techniques to aid the air traffic controller during peak demand periods. By scheduling aircraft in a given system in a different manner, delay, caused by congestion, could possibly be reduced at high density terminals even more than it has been reduced by the results obtained from previous studies. The approach taken in this study involves testing different heuristic scheduling algorithms, based on what has been done previously, to determine what extent total system delay can be reduced. The method of approach which was followed was based on a simulator which models aircraft movement between N major terminals. For each scheduling algorithm developed, hourly statistics related to the number of aircraft demanding service, average departure delay, and average arrival delay were calculated along with total system delay times for arriving and departing aircraft. The results obtained from these algorithms were analyzed and compared with the scheduling algorithm which resulted in a reduction in delay being examined in greater detail to determine whether or not such a schedule would actually be feasible and worthwhile.
- Improving the Efficiency of Hub Operations in a Less-than-Truckload Distribution NetworkBrown, Amy Michelle (Virginia Tech, 2003-04-22)The less-than-truckload (LTL) industry is highly competitive, with recent average profit margins less than 3%. LTL shipments are routed through a network of service centers and hubs. The performance of the entire LTL distribution network is highly dependent on the speed and accuracy of the hub operations. The focus of this research effort is to improve hub operations in order to reduce costs and increase service performance levels. Specifically, new approaches are investigated for assigning trailers to dock doors and sequencing the unloading of shipments at hubs. This thesis reviews current industry practices and available research literature on hub operations. Solution approaches for the trailer-to-door assignment and freight sequencing problems are presented along with case study results. The main performance measures are bottleneck time, total labor time, and total travel distance. For the trailer-to-door assignment problem, also referred to as the hub layout problem, the three approaches investigated are the original approach, a semi-permanent approach, and a dynamic approach. For the freight sequencing problem, the five approaches evaluated are trailer-at-a-time, trailer-at-a-time with offloading, nearest neighbor within a group, nearest neighbor within a shared group, and nearest neighbor. The approaches are implemented in C++ and analyzed using data from a regional LTL carrier. The case study results indicate that the dynamic layout performs significantly better than the original and semi-permanent layout for total distance, total labor time, and bottleneck time. For total distance and total labor time, the dynamic layout with nearest neighbor sequencing is the preferred approach. For bottleneck time, the dynamic layout with trailer-at-a-time with offloading performs best, while the nearest neighbor sequencing approach performs almost as well. In general, the case study results indicate that a dynamic layout with either a trailer-at-a-time with offloading approach or a nearest neighbor approach offers the largest potential for improvement. The assumptions and results of the hub layout and freight sequencing approaches are further evaluated using a simulation model. The simulation model indicates that a dynamic layout with nearest neighbor sequencing offers the largest potential for improvement in a more realistic environment with probabilistic and dynamic events. The simulation results also indicate that the trailer-at-a-time with offloading approach may need to be modified to account for more realistic dock conditions. In summary, the approaches explored in this research offer significant opportunity to improve hub operations through reducing bottleneck time, total labor time, and total travel distance.
- Measuring Leanness of Manufacturing Systems and Identifying Leanness Target by Considering AgilityWan, Hung-da (Virginia Tech, 2006-07-12)The implementation of lean manufacturing concepts has shown significant impacts on various industries. Numerous tools and techniques have been developed to tackle specific problems in order to eliminate wastes and carry out lean concepts. With the focus on "how to make a system leaner," little effort has been made on determining "how lean the system is." Lean assessment surveys evaluate the current status of a system qualitatively against predefined lean indicators. Lean metrics are developed to quantify performance of improvement initiatives, but each metric only focuses on one specific area. Value Stream Maps demonstrate the current and future states graphically with the emphasis on time-based performance only. A truly quantitative and synthesized measure for overall leanness has not been established. In some circumstances, being lean may not be the only goal for manufacturers. In order to compete in the rapidly changing marketplace, manufacturing systems should also be agile to respond quickly to uncertain demands. Nevertheless, being extremely agile may increase the cost of regular operations and reduce the leanness of the system. Similarly, being extremely lean may reduce flexibility and lower the agility level. Therefore, a manufacturing system should be agile enough to handle the uncertainty of demands and meanwhile be lean enough to deliver goods with competitive prices and lead time. In order to achieve the appropriate leanness level, a leanness measure is needed to address not only "how lean the system is" but also "how lean it should be." In this research, a methodology is proposed to quantitatively measure leanness level of manufacturing systems using the Data Envelopment Analysis (DEA) technique. The production process of each work piece is defined as a Decision Making Unit (DMU) that transforms inputs of Cost and Time into output Value. Using a Slacks-Based Measure (SBM) model, the DEA-Leanness Measure is developed to quantify the leanness level of each DMU by comparing the DMU against the frontier of leanness. A Cost-Time-Value analysis is developed to create virtual DMUs to push the frontier towards ideal leanness so that an effective benchmark can be established. The DEA-Leanness Measure provides a unit-invariant leanness score valued between 0 and 1, which is an indication of "how lean the system is" and also "how much leaner the system can be." With the help of Cost-Time Profiling technique, directions of potential improvement can be identified by comparing the profiles of DMUs with different leanness scores. The leanness measure can also be weighted between Cost, Time and Value variables. The weighted DEA-Leanness Measure provides a way to evaluate the impacts of improvement initiatives with an emphasis on the company's strategic focus. Performing the DEA-Leanness measurement requires detailed cost and time data. A Web-Based Kanban is developed to facilitate automated data collection and real-time performance analysis. In some circumstances where detailed data is not readily available but a Value Stream Maps (VSM) has been constructed, the applications of DEA-Leanness Measure based on existing VSM are explored. Besides pursuing leanness, satisfying a customer's demand pattern requires certain level of agility. Based on the DEA-Leanness Measure, appropriate leanness targets can be identified for manufacturing systems considering sufficient agility level. The Online-Delay and Offline-Delay Targets are determined to represent the minimum acceptable delays considering inevitable waste within and beyond a manufacturing system. Combining the two targets, a Lean-Agile Performance Index can then be derived to evaluate if the system has achieved an appropriate level of leanness with sufficient agility for meeting the customers' demand. Hypothetical cases mimicking real manufacturing systems are developed to verify the proposed methodologies. An Excel-based DEA-Leanness Solver and a Web-Kanban System have been developed to solve the mathematical models and to substantiate potential applications of the leanness measure in real world. Finally, future research directions are suggested to further enhance the results of this research.
- A simulation game for wildlife management planningGuynn, David C. (Virginia Polytechnic Institute and State University, 1973)A computer simulation model of the planning process of the wildlife management agency of an eastern sta te was constructed. The model is constructed in the form of a management game for inservice training and classroom use. The player of the game formulates a five-year operating plan for the mountainous region of the state. The plan is implemented on an annual basis and annual reports are issued to reflect how well scheduled activities. meet public demands. The player is allowed to modify the five-year operating plan after examination of the annual report. Components of the wildlife management system included in the model are: land acquisition, hunter access, habitat improvement, stocking programs, coordination with forestry practices, public relations, hunting regulations, and budget calculations. Public reaction to the planner's policies is provided on an annual basis in addition to output concerning mandays of hunting, population levels, estimates of legal and illegal harvest, and budget constraints for the following year. Verification of the model was based on subjective tests of reasonableness performed by those considered knowledgeable about the real system. Operational instructions are provided for those wishing to use the game and an example five-year run of the game is presented as a guide for use.
- Vendor Managed Inventory: A new approach to supply chain managementGandhi, Ujval (Virginia Tech, 2003-12-16)The Global Supply Chain Forum (Stanford Global Supply Chain Forum Web Resource, http://www.stanford.edu/groups/scforum) defines supply chain management (SCM) as “Supply chain management is the integration of key business processes from end user through original suppliers that provides products, services and information that add value for customer and other stakeholders.” The rapid development of the Internet has dramatically changed the traditional definitions of manufacturer, suppliers and customers. Newer approaches to supply chain management attempt to organize the supply chain as a network of cooperating intelligent agents, each performing one or more supply chain functions and each coordinating actions with one another. This research is aimed at creating a viable model of a single manufacturer single supplier collaborative supply chain system using a Vendor Managed Inventory (VMI) system. The research further uses known inventory performance parameters to performance benchmark the VMI system with traditional push-pull systems, develop a collaborative forecasting spreadsheet solution and a best alternative ordering policy amongst EOQ, Monthly, JIT and VMI policies under known lead time and a variety of demand distribution functions.