Lean Analysis Framework for Waste Management: A Case of Indonesian Textile Company

Abstract

This study aims to propose a lean analysis framework for waste management and to test it into the field case. The proposed framework was applied in a weaving process of a textile company in Indonesia. The seven classical Lean wastes were identified using value stream mapping (VSM). The result was then analyzed using the waste assessment model within which waste relationship matrix (WRM) and waste assessment questionnaire (WAQ) according to the answers of the head of weaving division studied. The major source of wastes was then determined utilizing the value stream analysis tool (VALSAT). In order to thoroughly examine the root cause of such dominant wastes and to propose corrective plans to minimize the waste, a fishbone diagram was used. As the main result, this study provides a lean waste analysis framework with examples to orientate managers about wastes. Particularly in our specific case, the results demonstrate that the waiting and defect become the most significant wastes that need to be treated. These findings allow a company to organize its activities and select tools or practices to optimize its efforts to create proper corrective plans in eliminating waste. In our study, the plans include periodic maintenance of weaving machines, clear division of tasks on the distribution of weft yarns, and eliminating unnecessary activities. In addition, it is mandatory to ensure the quality of warp yarns delivered to the weaving process as well as to perform a periodic calibration of equipment on weaving machines. This study advances in the theoretical and practical field by showing a structured way to incorporate lean analysis that can be adopted for any organization.

Implementation of Lean Construction to Eliminate Waste: A Case Study Construction Project in Indonesia

“…Each question has three answers and each was assigned a weight of: 1, 0.5 or zero. The questions were then categorized into four groups of man, machine, material and method since each relates to one of these categoriesThe complete steps are as follows [35]: for each type of waste j (2) where: 𝑆 𝑗 is the total score of the waste, and k ranges between 1 and 68. c. Counting the number of non-zero cells in each column to obtain the frequency ( 𝑓 𝑗 ) for each type of waste d. Calculating the initial indication factor of each type of waste using Equation (3).…”