Analisis Human Error dengan Pendekatan Metode SHERPA dan HEART pada Produksi Batu Bata UKM Yasin

Kesalahan kerja yang terjadi banyak diakibatkan oleh manusia itu sendiri yang disebut dengan human error. Human error yang sering terjadi dalam kegiatan produksi bisa merugikan perusahaan dalam mewujudkan efektivitas dan efisiensi produksi. Oleh karena itu maka perlu dilakukan perbaikan performansi pekerja untuk mengurangi seringnya terjadi kesalahan kerja. Beberapa metode dalam mengidentifikasi human error diantaranya metode SHERPA dan HEART. SHERPA suatu metode kualitatif dalam menganalisis human error yang menjadikan task level sebagai dasar inputnya. Sedangkan HEART adalah metode dalam menentukan resiko human error yang cepat, sederhana dan gampang dimengerti oleh para engineers dan juga human factors specialists. UKM Yasin merupakan salah satu UKM yang bergerak dalam produksi batu bata di Kota Batam. Proses pembuatan batu bata melalui beberapa tahapan yaitu proses pencetakan, proses pengeringan dan proses pembakaran. Permasalahan yang masih sering terjadi yaitu kesalahan saat melakukan pekerjaan yang berakibat terhadap kecelakaan kerja dan juga berpengaruh terhadap output produksi batu bata, hal ini disebabkan oleh human error. Hasil penelitian untuk rekomendasi yang akan diperlukan untuk mereduksi error pada proses produksi batu bata dengan metode SHERPA yaitu melakukan pemeriksaan secara teliti dan rutin terhadap masing-masing proses dan memberikan pelatihan secara berkala terhadap pekerja. Peluang terjadinya error dalam setiap aktivitas pekerjaan pada produksi batu bata dengan menggunakan metode HEART dimana nilai human error probability yang paling besar yaitu 0.16. Proses yang mungkin terjadinya human error dalam tahapan proses produksi batu bata di UKM Yasin melalui nilai Human Error Probability (HEP) tertinggi yaitu 0.544 yang terdapat pada proses pembakaran batu bata.

Human reliability analysis of high-temperature molten metal operation based on fuzzy CREAM and Bayesian network

Human errors are considered to be the main causation factors of high-temperature molten metal accidents in metallurgical enterprises. The complex working environment of high- temperature molten metal in metallurgical enterprises has an important influence on the reliability of human behavior. A review of current human reliability techniques confirms that there is a lack of quantitative analysis of human errors in high-temperature molten metal operating environments. In this paper, a model was proposed to support the human reliability analysis of high-temperature molten metal operation in the metallurgy industry based on cognitive reliability and error analysis method (CREAM), fuzzy logic theory, and Bayesian network (BN). The comprehensive rules of common performance conditions in conventional CREAM approach were provided to evaluate various conditions for high-temperature molten metal operation in the metallurgy industry. This study adopted fuzzy CREAM to consider the uncertainties and used the BN to determine the control mode and calculate human error probability (HEP). The HEP for workers involved in high-temperature melting in steelmaking production process was calculated in a case with 13 operators being engaged in different high-temperature molten metal operations. The human error probability of two operators with different control modes was compared with the calculation result of basic CREAM, and the result showed that the method proposed in this paper is validated. This paper quantified point values of human error probability in high-temperature molten metal operation for the first time, which can be used as input in the risk evaluation of metallurgical industry.

Efforts To Reduce Downgrade Of Steel Pipes In The Production Process Using The HEART Method

Pt X is a company that produces steel pipe of various shapes and size. In the production procces not only using machines but also using humans as operators. So in this case humans play an important role in maintaining the quality of production. The purpose of this study is to analyze the human error probability with Human Error Assessment and Reduction Technique method (HEART). HEART is a method designed as a fast and simple human reliability assessment in quantifying the risk of human error. From this research, it was found that 3 tasks had a high HEP value which caused the decline in pipe quality during the production process, namely task 3.2, 4.1 and task 3.4. Which has the highest HEP value on task 3.2, namely setting the machine with a value of 0,7680. The cause is due to the lack of operator expertice and the center roll was not carried out when installing it, so that training is needed to increase operator expertice.

Human reliability analysis in de-energization of power line using HEART in the context of Z-numbers

Investigation reveals that a high percentage of incident causes are ascribed to some forms of human error. To effectively prevent incidents from happening, Human Reliability Analysis (HRA), as a structured way to represent unintentional operator contribution to system reliability, is a critical issue. Human Error Reduction and Assessment Technique (HEART) as a famous HRA technique, provides a straightforward method to estimate probabilities of human error based on the analysis of tasks. However, it faces varying levels of uncertainty in assigning of weights to each error producing condition (EPC), denoted as assessed proportion of affect (APOA), by experts. To overcome this limitation and consider the confidence level (reliability or credibility) of the experts, the current study aimed at proposing a composite HEART methodology for human error probability (HEP) assessment, which integrates HEART and Z-numbers short for, Z-HEART. The applicability and effectiveness of the Z-HEART has been illustrated in the de-energization power line as a case study. Furthermore, a sensitivity analysis is fulfilled to investigate the validity of the proposed methodology. It can be concluded that Z-HEART is feasible for assessing human error, and despite the methodological contributions, it offers many advantages for electricity distribution companies.

Assessment of Human Reliability Under the Conditions of Uncertainty: SPAR-H Methodology Interpreted in Terms of Interval-Valued Probabilities

The well-known standardized plant analysis risk-human reliability (SPAR-H) methodology is widely used for analysis of human reliability in complex technological systems. It allows assessing the human error probability taking into account eight important groups of performance shaping factors. Application of this methodology to practical problems traditionally involves assumptions which are difficult to verify under the conditions of uncertainty. In particular, it introduces only two possible values of the nominal human error probabilities (for diagnosis and for actions) which do not cover the whole spectrum of the tasks within operator's activity. In addition, although the traditional methodology considers the probabilities of human errors as the random variables, it operates only on a single predefined type of distribution for these variables and does not deal with the real situations in which the type of distribution remains uncertain. The paper proposes modification to the classical approach to enable more adequate modeling of real situations with the lack of available information. The authors suggest usage of the interval-valued probability technique and of the expert judgment on the maximum probability density for actual probabilities of human errors. Such methodology allows obtaining generic results that are valid for the entire set of possible distributions (not only for one of them). The modified methodology gives possibility to derive final assessments of human reliability in interval form indicating “the best case” and “the worst case.” A few numerical examples illustrate the main stages of the suggested procedure.