The Bees Algorithm (BA) is a metaheuristic algorithm to find good solutions to optimisation problems in reasonable computing times. This paper is the first to report on the use of the BA to solve 9 combinatorial optimisation problems (COP) with more than 100 cities from TSPLIB rigorously to test the performance of the algorithm. The work employed a basic version of the BA for COP and TSPLIB datasets involving between 100 and 200 cities. The results obtained show that deviations from the best-found tour lengths for the datasets with 100 cities and 200 cities were approximately 2.5% and 7.5%. The reason for this jump in deviations was that the number of iterations was kept constant for all experiments while the solution space increased factorially with the number of cities. This research can be replicated and modified through Google Colab.

PT X merupakan pabrik yang memproduksi beragam produk kopi. Proses produksi pada perusahaan tersebut terdiri dari roasting, mixing, grinding, dan packing (1,2,3,4). Perusahaan ini masih merupakan perusahaan padat karya. Pada pengamatan awal, terlihat pekerja memiliki posisi kerja yang kurang baik sehingga ada resiko bahaya muskuloskeletal, sehingga akan dilakukan pengambilan data dengan menggunakan wawancara dan kuesioner Cornell Musculoskeletal Discomfort Questionnaires (CMDQ). Resiko bahaya muskuloskeletal yang teramati ada pada beberapa area tubuh, seperti punggung bawah, betis, dan lainnya. Analisa postur tubuh dengan metode Rapid Entire Body Assessment (REBA) dan Rapid Upper Limb Assessment (RULA) digunakan pada penelitian ini. Metode REBA digunakan untuk analisa postur pada proses roasting, mixing, grinding, dan packing 4, sedangkan packing 1, 2, dan 3 menggunakan metode RULA. Pada hasil analisa REBA, postur yang paling berbahaya adalah pada stasiun 4 dengan nilai 9, sedangkan postur yang paling berbahaya pada analisa RULA adalah pada stasiun packing 1 dan 2 dengan nilai 6. Pemberian solusi perbaikan dilakukan terhadap stasiun yang dianggap berbahaya bagi pekerjanya, yakni stasiun roasting, mixing, grinding, packing 1, 2, dan 4. Solusi yang diberikan berbeda-beda tergantung pada kebutuhan, diantaranya adalah dengan mengubah metode kerja dan menggunakan troli yang dapat disesuaikan.   Kata Kunci: Cornell Musculoskeletal Discomfort Questionnaires (CMDQ), Gangguan Muskuloskeletal, Rapid Entire Body Assessment (REBA), Rapid Upper Limb Assessment (RULA)

Remanufacturing is widely recognised as a key contributor to the circular economy (CE) as it extends the in-use life of products, but its synergy with Industry 4.0 (I4.0) has received little attention when compared to manufacturing. An agglomeration of I4.0 technologies and methodologies is reflected in the emerging digital twin (DT) concept, which has been identified as a life-extending enabler. This article captures the design and demonstration of a DT model that optimises remanufacturing planning using data from different instances in a product’s life cycle. The model uses a neural network for remaining useful life predictions and the Bees Algorithm for decision making within a DT. The model is validated using a real case study. The findings support the idea that intelligent tools within a DT can enhance decision-making if they have visibility and access to the product’s current status and reliable remanufacturing process information.

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