Lean management has generated new approaches to reduce non-value-adding activities in different sectors of the economy, including in higher education systems. Lean principles in higher education institutions (HEIs) contribute positively to sustainability performance. The current study aims to: (a) assess waste in HEIs based on lean principles and even their potential effect on sustainability; (b) establish the relationship among wastes; (c) develop a structural model using Interpretative Structural Modeling (ISM); (d) carry out the Matrice d’impacts Croisés Multiplication Appliqué Àun Classement (MICMAC) analysis. In Phase 1 of this study, the identification of waste modes in HEIs was established. In Phase 2, risk assessment of each waste mode was conducted using the waste-Failure Mode and Effect Analysis (w-FMEA) technique. In Phase 3, ISM-MICMAC was used to identify relationships among critical waste modes. The results showed that eighteen waste modes were identified as critical in HEIs—with six waste modes being autonomous determinants; four were dependent determinants, four were linkage determinants, and four were driver determinants. This study is expected to help academicians and practitioners understand HEI’s waste types by listing the critical wastes, mapping their interrelationship, identifying the driving power and dependence, and proposing mitigation actions. It will also contribute to the growing body of literature highlighting the waste in HEIs.
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Lean is a philosophy that is seen as a solution to resolve the problem of efficiency in various industries. It can be used to eliminate all forms of waste in the workplace. The implementation of lean is not only applied in manufacturing but is very important to be applied in other fields, such as in Higher Education Institution. Studies on the topic of lean in the workplace have been carried out, but most of the study has been conducted within a manufacturing context. This study aims to determine the type of waste that is most important to be eliminated first by using the Waste Assessment Model and find the root of the waste problem. This study developed the relationship between waste and find out the effect of waste on each other in Higher Education Institution that focused on teaching and learning process. The steps of this study consist of three-step, such as waste identification, waste assessment, and root cause analysis. From data collection show that there are 46 forms of waste in the teaching and learning process. The results of the Waste Relationship Matrix showed three types of waste must be removed first, namely overproduction, defects, and non-utilized talents. 5-Why’s is used to find out the root causes of waste which is the most important to be eliminated first in the teaching and learning process.
Perkembangan teknologi menuntut segala sesuatu dilakukan serba cepat, praktis, dan efektif efisien. Hadirnya dompet digital menggunakan sistem elektronik berbasis internet, sistem kerja dapat meringkas segala transaksi keuangan dibandingkan dengan transaksi konvensional. Penelitian ini menganalisis faktor-faktor yang mempengaruhi pemilihan penggunaan dompet digital di Kota Surabaya, dengan melakukan analisis cluster pada profil responden yang didapat dan analisis diskriminan untuk menemukan perbedaan tiap cluster. Dilakukan analisis faktor dari variabel-variabel yang telah ditentukan sehingga didapatkan hasil kemudahan, kemampuan finansial, kecepatan bertransaksi, keamanan, promosi, dan pengaruh sosial berpengaruh terhadap pemilihan penggunaan dompet digital. Terbentuk 2 cluster responden, sedangkan yang menjadi pembeda adalah tingkat penghasilan oleh konsumen.
With the increasing complexity of the process industry, having excellent maintenance management is essential for manufacturing industries. Various parts that interact and interdependent with each other make a well-planned maintenance strategy is one of the major challenges facing by industry. The whole system could be interrupted just simply because of the failure of a component. Therefore, a review of a maintenance strategy must be done from a system perspective. It is suggested that the optimal preventive maintenance time interval is not only determined by the lowest maintenance cost of each machine but also its impact on the whole system. Two main indicators that can accommodate the system perspective are reliability and revenue. A large number of machines and the array of machines can be synthesized in the reliability indicator. Moreover, the creation of maximum revenue is always the main goal for a business. The best maintenance strategy will be determined from the revenue obtained by a process industry. The process industry discussed in this study is a flour mill which is very well known in Surabaya. This study applied a hybrid simulation to solve this problem. Monte Carlo simulation was used to observe the machine individually and the results are reviewed using the application of System Dynamics. Three improvement scenarios were proposed in this simulation study. Scenario 2 was chosen as the best scenario because it was able to generate the highest revenue at the end of the period. Scenario 2 recommends setting the preventive maintenance time interval considering resource availability.
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