1. ABOUT THE DATASET -------------------- Title: Operational data from Indonesian batik companies Creator(s): Ida Nursanti[1,2], Alison McKay[1], Richard Chittenden[1] Organisation(s): 1. University of Leeds. 2. Universitas Muhammadiyah Surakarta Rights-holder(s):Unless otherwise stated, Copyright 2024 University of Leeds Publication Year: 2024 Description: The operational data includes historical records of freshwater use for equipment cleaning and processing, along with batch sizes for each stage of the batik production process across four different companies. Since the data for each operation varies, some are presented as probability distributions, with their distributions and parameters determined using Arena software's input analyzer. This data was used to develop a simulation model that predicts water used in the batik production process based on product design. Cite as: Nursanti, et al. (2024) Dataset for 'Operational data from Indonesian batik companies'. University of Leeds. [Dataset] https://doi.org/10.5518/1600. Related publication: Nursanti, et al., An approach for integrating water use assessment into the design processes of the Indonesian batik industry, Journal of Cleaner Production, 2024 (Submitted). Contact: ida.nursanti@ums.ac.id 2. TERMS OF USE --------------- This dataset is licensed under a Creative Commons Attribution 4.0 International Licence: https://creativecommons.org/licenses/by/4.0/. 3. PROJECT AND FUNDING INFORMATION ---------------------------------- Title: An approach for assessing water use in the Indonesian batik industry Dates: 1 October 2024 - 30 March 2024 Funding organisation: Directorate General of Higher Education, Ministry of Education and Culture, Republic of Indonesia Grant no.: 4. CONTENTS ----------- File listing operational_data_batik_company1 operational_data_batik_company2 operational_data_batik_company3 operational_data_batik_company4 5. METHODS ---------- The dataset was collected through observations conducted at four batik companies in Central Java, Indonesia, over one month at each company from June 2022 to November 2022. Due to COVID-19 restrictions, data collection was supported by staff from the Centre for Logistics and Industrial Optimisation Studies at Universitas Muhammadiyah Surakarta, specifically Erza Maldini and Rafi Faizurahman. As the data for each operation varies, some are represented as probability distributions, with their parameters determined using Arena software's input analyzer.