From Micro to Macro: A Comprehensive Study of Lean Manufacturing Tools in Tanzanian Industries

ABSTRACT The study aimed to establish the adoption status of tools and practices, drivers, and barriers for Lean Manufacturing (LM) for the Tanzanian context based on the industry size. The study adopted a survey research design. A purposeful sampling technique was deployed to collect responses from micro, small, medium, and large manufacturing industries. A total of 256 responses were received. Upon data cleaning, a total of 243 responses remained for further analysis. SPSS version 27 was used to analyze descriptive statistics such as mean and inferential statistics such as ANOVA. The results indicate the growing adoption of Lean Manufacturing across industries, from micro to large industries. The adoption of Lean Manufacturing for large industries is 75.1%, for medium industries is 66.7%, for small industries is 54%, and 50% for micro industries. The average adoption for all industries is 61.5%. The specific Lean practices vary by industry size; common practices include 5 s, visual management, and concurrent engineering with larger industries using more complex lean practices like cellular manufacturing. Moreover, the study indicates that drivers and barriers for Lean Manufacturing vary based on the size of the manufacturing industry. The study will guide those who wish to implement Lean Manufacturing in Tanzania and other countries with similar characteristics and challenges.

Authors

Institutions

Publication Details

Journal
Engineering Reports
Published
2025-02-01
DOI
https://doi.org/10.1002/eng2.70020
Citations
5
Primary Topic
Quality and Supply Management
Type
article
Field-Weighted Citation Impact
11.42
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

From Micro to Macro: A Comprehensive Study of Lean Manufacturing Tools in Tanzanian Industries

Francis D. Sinkamba, Juma M. Matindana, Mussa I. Mgwatu
5 citations
Engineering Reports
Quality and Supply Management
11.42
article

From Micro to Macro: A Comprehensive Study of Lean Manufacturing Tools in Tanzanian Industries

Francis D. Sinkamba, Juma M. Matindana, Mussa I. Mgwatu
article en
5 citations

Abstract

ABSTRACT The study aimed to establish the adoption status of tools and practices, drivers, and barriers for Lean Manufacturing (LM) for the Tanzanian context based on the industry size. The study adopted a survey research design. A purposeful sampling technique was deployed to collect responses from micro, small, medium, and large manufacturing industries. A total of 256 responses were received. Upon data cleaning, a total of 243 responses remained for further analysis. SPSS version 27 was used to analyze descriptive statistics such as mean and inferential statistics such as ANOVA. The results indicate the growing adoption of Lean Manufacturing across industries, from micro to large industries. The adoption of Lean Manufacturing for large industries is 75.1%, for medium industries is 66.7%, for small industries is 54%, and 50% for micro industries. The average adoption for all industries is 61.5%. The specific Lean practices vary by industry size; common practices include 5 s, visual management, and concurrent engineering with larger industries using more complex lean practices like cellular manufacturing. Moreover, the study indicates that drivers and barriers for Lean Manufacturing vary based on the size of the manufacturing industry. The study will guide those who wish to implement Lean Manufacturing in Tanzania and other countries with similar characteristics and challenges.

Engineering ReportsVol. 7(2)
University of Dar es Salaam (TZ), Institute of Accountancy Arusha (TZ)
Openalex Percentile: Top 2%
Quality and Supply Management
11.42
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.