- 學位論文
團隊心智負荷與團隊績效模式之研發與應用
The Development of Team Mental Workload and its Application on Improving Team Performance
摘要
核能電廠的維修和監控作業及飛機維修和檢驗工作的安全性仰賴團隊作業來達成安全目標，先前已有諸多研究致力發展提昇人為績效的方法及建立人為失誤分析流程，但人為失誤仍存在核能電廠維修及監控作業及飛機維修過程中，且缺少有效的預警及預防措施。為了有效地避免人員在核能電廠作業及飛機維修工作的人為疏失及增進工作的績效與安全，本研究首先調查核電廠維修人員在執行數位式及類比式的飼水系統時，其心智負荷表現。而過去研究顯示低心智負荷的工作環境會造成人員的績效降低，故本研究首先發展低心智負荷即時預警模式（Real-time warning model；RTWM），使人員在低心智負荷作業下仍能有良好的績效表現。另外，在預防航空維修作業的人為失誤上，本研究發展飛機維修工作的線上維修輔助平台（On-line maintenance assistance platform；On-line MAP），以增進維修人員對於維修風險的知識。本研究方法，基於過去文獻找出影響心智負荷的要因，以發展問卷及分析模式，比較人員在執行數位式及類比式儀控系統的心智負荷差異。另外，應用群組資料處理演算法（GMDH）及模糊推論以發展心智負荷即時預警模型（RTWM）。最後，調查某航空公司的關鍵維修績效影響要因外（Performance shaping factors；PSFs），並考量每一維修程序所潛藏的風險大小、人為失誤及失誤可能對系統及人員造成的影響，發展線上維修輔助平台（On-line MAP）。在心智負荷即時預警模型發展上，本研究以個人電腦訓練分析模擬器進行電腦化團隊工作的實驗，實驗環境為模擬核能電廠現場監控作業的狀況。透過實驗的進行以收集三十九位受測者的心率變化率及人員的作業績效（錯誤率及反應時間）。在線上維修輔助平台（On-line MAP）的建構上，收集維修專家經驗，使維修輔助平台的功能包含：人為失誤對系統與個人所帶來的影響、潛在人為失誤所隱含的嚴重度，圖形化的資訊。研究結果指出：（1）核能電廠的數位系統設計可以降低人員心智負荷及減少人員的操作時間，（2）心智負荷即時預警模式的驗証結果，此模式可以有效的預防運轉員在低心智負荷作業下的績效降低，（3）線上維修輔助平台所提供的風險知識除了增進維修訓練中維修人員對於人為失誤及風險的認知外，同時滅少維修人員的心智負荷及維修災害。
並列摘要
Safety in the complex industry such as monitoring, maintenance and inspection tasks in nuclear power plants (NPPs) and aircraft industry relies on high team performance. Although various preventive methods have been developed, human error still exists. In order to increase monitoring, maintenance and inspection safety, the aims of this study are to (1) evaluate the mental workload of maintenance engineers at a NPP in Taiwan according to the factors affecting the mental workload, (2) develop a real-time warning model (RTWM) by assessing team performance (response time, error rates) and mental workload, and (3) develop an on-line maintenance assistance platform (on-line MAP) for technician training and performing aircraft maintenance tasks. The research methods include (1) designing the questionnaire and field study on mental workload comparison during the on-line maintenance of digital and analog systems, (2) applying the group method of data handling (GMDH) algorithm to predict team performance and the fuzzy inference to construct the RTWM, and (3) considering the impact of the performance-shaping factors (PSFs) and human error as well as error effect in each procedure to develop an on-line MAP. To model RTWM, experiments were conducted on computer-supported cooperative work (CSCW) in the personal computer transient analyzer (PCTRAN) simulator. The simulator and teamwork were designed to simulate real tasks of the control room of a new nuclear power plant in Taiwan. In addition, important physiological parameters, the NASA-TLX questionnaire, team response time, and team error rates were collected from 39 participants. Moreover, to design the on-line MAP, the functions include (1) native language explanations, (2) the effects of human errors on system and human, (3) human errors relative to seriousness rank and frequency, and (4) graphic information aids in each removal and installation procedure. The results indicated (1) mental workload was lower in maintaining digital systems than that in analog systems, (2) the proposed RTWM can efficiently predict teamwork performance to maintain appropriate mental workload as well as ensure system safety, and (3) the proposed on-line MAP may potentially not only increase risk knowledge, situation awareness, and performance of workers but also decrease workload and maintenance incidents.