Green Lean Six Sigma model for waste reduction of raw material in a nectar manufacturing company of Lima, Peru

Abstract

Purpose: Food waste is a latent problem for society, one of the main causes being poor management of the operating processes within the food industry, which is the main reason the present research aimed to reduce raw material waste in a nectar factory.

Design/methodology/approach: The methodology led to carrying out an experimental investigation where a Green Lean Six Sigma Model was applied, whose foundation was the use of tools such as Environmental Value Stream Mapping (E - VSM), DMAIC (Define - Measure - Analyze - Improve - Control), Poka Yoke and DOE (Design of Experiments), the data obtained were exposed to an inferential statistical analysis using tests such as Anderson - Darling and T-Student.

Findings: As a final result, a waste reduction of 2.23% was obtained, which is equivalent to approximately 120 kg of useful raw material, in addition the environmental impact was reduced by 2.2%, waste costs were also reduced by approximately 5.5% and produced an increase in global productivity by 2.4%.

Research limitations/implications: It is shown that the application of methodologies such as Green, Lean and Six Sigma in the food industry present benefits during and after the application of the model; such as preventive control of waste, standardization in processes; benefits that, in coordination with an organizational culture of continuous improvement, can significantly improve the current state of companies.

Practical implications: The positive obtained results support the methodology proposed by the authors to reduce the waste of agricultural raw material. It is expected to be a benchmark for other similar organizations that seek to generate greater productivity in line with the search for environmentally sustainable operations.

Originality/value: This is one of the first studies that aims to reduce the waste of raw materials in food processing companies, considering aspects of mitigating environmental impact.