Lean production for technology management: Increasing production, reducing waste and quality improvement strategies in a plastic bags manufacturing facility

Abstract

Given the pressures generated by the global economy, the manufacturing sector is faced with the problem of continually improving production rates and quality while cutting costs. The pressures are especially keen in the smaller manufacturing plants where resources are scant, margins are small, and skilled labor is in short supply. The introduction of Programmable Logic Controllers (PLCs) in recent years has proven to be an important innovation to the production process, resulting in improved production and quality. However, any manufacturing process is subject to a large number of factors that are not necessarily sensitive to or controlled by a PLC. The application of relatively simple algorithms reflecting the complexity of a given production process is not likely. This project focused on a small manufacturer of plastic bags to identify the critical and non-critical factors of production and develop a strategy for the firm to manage those critical factors in order to improve production rates and quality while decreasing waste. This required the mapping of the production process, the identification of those elements that have the greatest impact on production rate and quality, and the development of a technology management system to monitor and control these sensitive elements. A systems dynamics model describing the production system abstract relationships was also developed as a tool for determining cost, quality, and schedule impacts and an enterprise perspective of the ROIC of the production system. The results of the project demonstrated a strategy that could achieve all three objectives for the company, namely increased productivity, quality, and reduced waste, all of which drive bottom line financial improvements, a key performance outcome in any lean enterprise.

Analysis of lean manufacturing strategy using system dynamics modelling of a business model

“…As initially targeted, the simulation findings help to understand how the case company might perform under the strategy of lean manufacturing improvements. The use of SD modelling in lean manufacturing-related research has been on-going (Thun, 2004; Hallam et al , 2009; Ali and Deif, 2016; Omogbai and Salonitis, 2016; Gupta et al , 2018; Omogbai and Saloniti, 2017). The approach taken in the current study is different because a high-level analysis of the operational dynamics is undertaken, rather than a detailed one.…”

The Implementation of Six Sigma and DMAIC Methodology To Increase Productivity and Meet Customer Requirements

“…The benefits of six sigma include, assists in viewing data in a statistical viewpoint and business viewpoint, assists in root cause analysis, process control planning, project management and knowledge discovery (Kwak and Anbari, 2004). Defect tracking and prevention, organizational planning, mapping and improvement, simulations and experiments are also some of the activities associated with six sigma (Flannery et al 2010). Increased market share, business profitability, improved customer satisfaction is some of the many business benefits as a whole (Anthony, 2006).…”