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Industrial muda elimination is a major challenge that is faced by the experts in the day to day activities of production systems. Mostly there are seven types of industrial muda in lean systems such as Defects, Overproduction of things not demanded by actual customers, Inventories awaiting further processing or consumption, Unnecessary over-processing, Unnecessary motion of employees, Unnecessary transport and handling of goods, Waiting for an upstream process to deliver, or for a machine to finish processing, or for a supporting function to be completed. Every organization faces particular type of waste that occurs in day to day production activities. In order to find out the most influential lean waste based on the ranking, a survey has been conducted in 91 automobile industries based on the 5 point likerts scale to find the highly impacted lean muda. The survey results stating that 3 types of waste arising out of 7 waste which heavily affect the production system. Hence this work mainly deals with assessing the most deadly waste by ranking the major waste using the weighted average method in which each waste is assigned a weight. Based on the results, the major muda, which are identified that affects the production activities are discussed in detail and how this muda can be eliminated and incorporated with the production system are discussed

Lean Manufacturing is a manufacturing paradigm, when implemented, it gives an evolutionary change in the production environment. The selection of lean tools is the changing factor in implementing the lean strategy. Lean tools can be selected by prioritizing the lean tools depending on its ability to attack lean wastes. Lean wastes affect any production process. It is required to find the lean wastes at the earliest. This study was conducted in the steering knuckle manufacturing section of a manufacturing industry to identify the lean wastes in the production line. Lean wastes-Lean tools relationship matrix was developed to find the priority among the lean tools. The ranking method using weighted scoring method showed a new way of selecting the lean tools among the various options. It also provides a systematic procedure for the managers to select the right lean tools to reduce lean wastes.

Lean refers to the reduction of non-value added activities in industries. It focuses on seven types of lean waste. The significant challenge is to identify and reduce the major lean waste. With this objective, a survey was conducted in an international exhibition in India using a questionnaire. The collected data were analyzed using Analytic Hierarchy Process (AHP) software template to check consistency. Finding consistent results obtained in AHP satisfactory, ranking was carried out to find the major lean waste using fuzzy AHP. After the identification of the major lean waste, the major contributing factors for the waste were ranked using the Binary Logistic Regression (BLR). These contributing factors were further investigated for the waste elimination in the automobile component manufacturing industries.

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