Cycle_Time_Reduction

DBMA620 Effective Financial and Operational Decision Making End of Seminar Project: Cycle Time Reduction TABLE OF CONTENTS 1.0 Executive Summary ................................................................................................ 3 2.0 Problem Statement.................................................................................................. 4 3.0 Project Objectives………………………………………………………………………….5 4.0 Final Project Description (Abstract)…………………………………………….....6 5.0 Conclusions ..................................................................................................................8 6.0 Lessons Learned…………………………………………………………………………….9 7.0 Recommendations………………………………………………………………………..10 8.0 References……………………………………………………………………………………11 1.0 Executive Summary Companies must recognize the need to streamline manufacturing processes and cut production costs to effectively do business in an increasingly competitive world marketplace. Playing an important part in this effort to constantly improve productivity and quality throughout the organization, Six Sigma techniques have been put into effect, identifying problem areas and removing defects and process variations. Most Quality Assurance Departments, maintain a Calibration certification program in accordance with ISO 9001. It is essential, therefore, that calibration be accomplished accurately and in a timely manner if employees are to perform efficiently and production schedules are to be met. The goal of the project is to reduce the mechanical calibration cycle time and backlog. Research and data collection enabled the team to apply the four basic Six Sigma Methodologies, Measurement, Analysis, Improvement and Control, to attack and resolve the problems. Once the actual causal factors were identified and the required process improvements. Were put into effect, lab efficiencies increased resulting in a sizable cost savings per year. 2.0 Problem Statement This problem concerns only the Mechanical Calibration Laboratory and the problems currently encountered in the mechanical calibration process. This is just one of many important managerial challenges facing our work organization. This includes extremely long cycle times and high backlog counts, contributing to production delays, as well as high processing and tracking costs. Originally, our team planned to investigate one area of mechanical calibration, namely special Tooling. However, data analysis revealed that special tooling comprised a disproportionately small number of items requiring calibration. The project scope was then expanded to include all mechanical calibration. Calibration of Measurement and Test Equipment (MTE) is a requirement of Quality Systems in compliance with ANSI/ISO 9001 and MIL-Q-9858A. Generally, companies divide MTE calibrations into two functional groups, Mechanical and electrical. The primary issues with the current mechanical calibration process are the extremely long cycle times and the high backlog counts, both contributing to production delays and high processing and tracking costs. Unfortunately, previous attempts to improve the process, overtime, outsourcing, and off-loading work to the EMC did not rectify the problem. Additionally, the process is not inherently self-guided thus forcing the customer to regularly monitor, expedite, and "push" the work through the system. The historic mechanical calibration mean time of 24 working days is incompatible with customer requirements. Moreover, the calibration backlog maintained by the mechanical Lab averaged 150 units per month. These averages for equipment calibration cycle time and backlog must be significantly reduced to achieve acceptable earned value, customer satisfaction, and work standards. 3.0 Project Objectives Originally the project objective focused on the investigation and improvement of The calibration cycle time as it related to Special Tooling, a subset of mechanical calibration. However, after collecting and reviewing historical data it was discovered That the actual quantity of Special Tooling processed in the lab was quite Small (average of 189 units per year) in relation to the total number of mechanical Items requiring calibration (average 1611 units per year). Subsequently, the project scope was expanded to include all equipment requiring mechanical calibration In order to maximize the process improvement return on investment. After project redefinition, the specific objectives were: 1) Reduce the calibration cycle time for all mechanical hardware from 24 working days to a maximum of 8 working days. 2) Reduce the calibration backlog from an average of 150 units to fewer than 25 per month. 3) Reduce calibration operation and collateral processing costs. Six Sigma breakthrough strategies and the four basic methodologies of Measurement, Analysis, Improvement, and Control were utilized to attack the Problem (Landy & Conte). However, before actual work began, the first strategy to ensure project success was forming the right team of key individuals intimately involved with, and responsible for, the process under investigation. Eventually, the process owner was added to the team to ensure data availability and provide historical process information and perspective. 4.0 Final Project Description The measurement phase began with the manual collection of historical and current data to gain an overall quantitative state of the process and to begin to help identify important preliminary process metrics and variables. Data sets from the METRIC database were eventually obtained and analyzed using Minitab. This data confirmed what the manually collected data suggested. A Pareto chart (Kirkpatrick, D. L) was generated to determine which area/function within the entire calibration process (from customer hardware pick-up/delivery, through property management, calibration and redeployment) was driving the cycle time. Clearly, the calibration element was the culprit with an average cycle time of 24.3 working days. (Calibration turn-around times ranged from 1 to over 130 days). The second Closest processing time was through Property Management, averaging 3.5 days. For purposes of this study, cycle times were calculated based on company’s four day work week. Therefore, Fridays through Sundays, as well as holidays were excluded and not counted. A detailed Mechanical Calibration process map was then developed with key input process variables (KPIVs) and key process output variables (KPOVs). The process map (see Appendix B) was very helpful in illuminating a number of previously undefined steps required to facilitate the process. Surprisingly, the process map proved to be an extremely beneficial tool. A Characteristic Selection Matrix (CSM) and Failure Mode and Effect Analysis (FMEA) were generated based on the Process Map. The resulting highest significant Rank and Risk Priority Numbers (20.5% and 640respectively) were associated with, and related to, the Backlog Shelf. The FMEA also uncovered a number of other areas contributing to delays in the processing and calibration of equipment including incomplete/inadequate documentation and tracking. However, it became very clear that the backlog shelf was the main process bottleneck. The team began to focus in this area to determine what was causing the problem. An analysis was performed to determine if the backlog problem was manpower related. Based on data obtained from the Metrology Department (METRIC) database, on average, only42% of a man year was required to calibrate the total number of items submitted to the lab per year. Obviously, lack of manpower was not the problem. Hypothesis tests were then conducted by again extracting data from the METRIC database to evaluate operator efficiencies. These tests indicated that the technicians performed better than the standards in terms of calibration touch time. Further analysis and investigation ultimately revealed the casual factor responsible for the long calibration cycle times was a lack of process controls to effectively move items off the backlog shelf. In actuality, equipment was routed through the lab and placed on the backlog shelf and would just “sit “in the calibration queue. As the project moved into the improvement phase, most of the time and effort was spent resolving the backlog problem by focusing on tracking, schedule and control issues. The main improvements were, 1) Implementation of the TRAFIC System as a management tool to monitor, track and support calibration scheduling, 2) initiation of a backlog reduction plan, 3) issuance of a management directive establishing mechanical calibration cycle time metrics and standards Other general process improvements included, the revision and streamlining of shop order operations flow, customer education and training, and the development of a plan to facilitate the issuance of Calibration Not Required (CNR) labels by Property Management for Special Tooling. Other than equipment calibration standards for MTEs, there were no established or documented process specifications relating to cycle times, and operator efficiencies etc. Therefore, the team determined an acceptable mechanical calibration cycle time (turn-around time) to be 8 working days maximum with a target goal of 4 working days. Cycle time was defined as the time from the date of hardware receipt on the metrology incoming shelf to the date of delivery to the metrology outgoing shelf. These specifications were supported by Aero jet management and laboratory personnel. Process capability was determined using a lower specification limit of zero and an upper limit of eight. The lower limit was defined as immediate or same day turn-around time. An initial process capability analysis was performed based on historical data. According to the historical data, the Sigma value for actual long term capability was -1.31 and -0.89 (Cpk -0.32) for potential short term Capability. These Sigma values were obviously quite poor. 5.0 Conclusions Before the Six Sigma improvement process began, opinions varied as to the reasons for long cycle times in the Mechanical Calibration Laboratory. Speculation included a suspected lack of manpower, too many special tools overloading the lab, an inefficient delivery system, customer equipment "dumping", etc. In retrospect, these suppositions seem rather amusing after discovering the actual causal factors using the Six Sigma methodologies based on facts (data). The main factors driving the long cycle time and Backlog was, 1) A poor scheduling, tracking and control system and, 2) A lack of documented work standards and performance metrics for laboratory personal. After implementing the previously outlined process improvements, results were almost immediate and although, as one would expect moderate improvements, they were generally a result of, and attributed to, the Hawthorne Effect (Franke & Kaul). Lab efficiencies increased dramatically thereby eliminating or greatly minimizing:1) outsourcing, 2) EMC equipment transfer, 3) overtime. In addition, the need for customers to constantly monitor and expedite their work was virtually eliminated, as were the costs incurred and the time involved. A projected minimum cost savings of$113,000 annually, (this figure is conservative as it does not include hidden factory costs, or the costs associated with production delays/downtime) is expected from process improvements and increased lab efficiencies. 6.0 Lessons Learned When choosing a project, the Black belt candidate must be aware of the ramifications of working outside his/her immediate area. Although the Quality Assurance department was very cooperative and excellent support was received, barriers were encountered. Six Sigma strategies and intentions were unfamiliar to the department, therefore, a certain amount of suspicion and resistance was detected. This project was sincerely approached from the standpoint of process improvement, yet these efforts were initially perceived as the “airing of dirty laundry”. With time, this perception lessened as the Product Assurance group realized that there would be a genuine benefit to applying the Six Sigma methodologies. The human factors and the cultural changes involved in an improvement initiative effort of this magnitude cannot be underestimated. Finally, the team expressed concern that the process improvements would be enthusiastically implemented then, over time, regress back to the original state. Therefore, to further ensure sustainment of process improvements, it is suggested that specific project metrics should be compiled and reviewed by senior management on a monthly basis. A follow-up summary report would then be forwarded to in addition to the quarterly report now required. 7.0 Recommendations 1) One area worth investigating is the level loading of equipment input into the lab by shifting calibration due dates. If level loading could be accomplished, quantity variations would be minimized and scheduling/manpower could be more accurately predicted and managed. Currently the lab experiences large demand surges due to the varied quantity of hardware required for calibration every month. And as indicated, calibration demands over the year vary substantially from month to month. To remedy the problem, as the hardware from either of these months was received into the lab for calibration, the lab would appropriately "shift" the due date as required the process to balance the load would occur incrementally over the period of one year. Once implemented, the due dates would not have to be altered unless large quantities were introduced into, or removed from the system. 2) It is also recommended that the process improvements and knowledge gained through this project be applied and expanded to the Electrical Calibration Laboratory in the form of a Six Sigma project. 8.0 References Franke, R. H. & Kaul, J. D. (1978). The Hawthorne experiments: First statistical interpretation. American Sociological Review, 1978, 43, 623-643. Kirkpatrick, D. L. (1999). Techniques for evaluating training programs. Journal of the American Society of Training Directors. Landy, F. J., & Conte, J. M. (2006). Work in the 21st century: An introduction to industrial and Organizational psychology (2nd ed.). Boston: Blackwell. Six Sigma Project