An Influence Diagram Approach to Automating Lead Time Estimation in Agile Kanban Project Management

2021 ◽  
pp. 115866
Author(s):  
Eric Weflen ◽  
Cameron A. MacKenzie ◽  
Iris V. Rivero
Keyword(s):  
Project Management ◽  
Lead Time ◽  
Time Estimation ◽  
Influence Diagram ◽  
Diagram Approach

Lead time estimation for modular production plants

2017 ◽  
Vol 128 ◽  
pp. 96-106 ◽  
Author(s):  
Stefan Sievers ◽  
Tim Seifert ◽  
Marcel Franzen ◽  
Gerhard Schembecker ◽  
Christian Bramsiepe
Keyword(s):  
Lead Time ◽  
Time Estimation ◽  
Modular Production

LEAD TIME ESTIMATION IN A CONTROLLED SCREENING PROGRAM

1983 ◽  
Vol 118 (5) ◽  
pp. 740-751 ◽  
Author(s):  
JUDY S. CHEN ◽  
PHILIP C. PROROK
Keyword(s):  
Lead Time ◽  
Screening Program ◽  
Time Estimation

scholarly journals Comparison of PERT/CPM and CCPM Methods in Project Time Management

2021 ◽  
Vol 16 (03) ◽  
pp. 01-20
Author(s):  
Taynara Takami Narita ◽  
Caio Henrique Alberconi ◽  
Fernando De Souza ◽  
Lucas Ikeziri
Keyword(s):  
Project Management ◽  
Time Management ◽  
Completion Time ◽  
Computational Simulation ◽  
Time Estimation ◽  
Project Planning ◽  
Theory Of Constraints ◽  
Performance Variables ◽  
Project Completion ◽  
Critical Chain

Purpose: Evaluate and compare PERT/CPM and Critical Chain Project Management (CCPM) techniques, from the Theory of Constraints (TOC), in relation to indicators of delivery time estimation and reliability in meeting established deadlines. Theoretical framework: The research is based on the time management theory established by the PERT/CPM and CCPM methods. Design/methodology/approach: This work has an experimental character, using a method of computer simulation by applying the Promodel software. A fictitious project environment managed by PERT/CPM and CCPM techniques was modeled in order to evaluate and compare their performances in terms of estimation of, and compliance with, project completion deadlines. Findings: The results obtained showed that the CCPM method proved to be more effective in reducing project completion time and meeting established deadlines. Conversely, the PERT/CPM method increased planned project completion time by 189%. Research, Practical & Social implications: Many managers assume that the best approach to project planning, especially when aiming for short and reliable deadlines, is to allocate margins of safety to each scheduled activity. This research reinforced the already widely held perception of TOC that, due to certain ordinary human behaviors, local optimizations do not guarantee, and usually adversely effect, good global results. Originality/value: There is a lack of research comparing PERT/CPM and CCPM techniques through modeling and computer simulations of project environments subjected to certain degrees of uncertainty, particularly in terms of performance variables such as those studied here. The results of this research, therefore, address this opportunity, bringing to light comparative scenarios and explanations for the different behaviors observed. Keywords: Computational Simulation; Project Management; Goldratt; Critical Chain; CCPM; PERT/CPM.

A Study of the Critical Chain Project Management Method Applied to a Multiproject System

2019 ◽  
Vol 50 (3) ◽  
pp. 322-334 ◽  
Author(s):  
Robert Eduardo Cooper Ordoñez ◽  
Mario Vanhoucke ◽  
José Coelho ◽  
Rosley Anholon ◽  
Olívio Novaski
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Project Management ◽  
Time Estimation ◽  
Key Factors ◽  
Critical Chain Project Management ◽  
Management Method ◽  
Critical Chain ◽  
Critical Resources

In 1997, Eliyahu Goldratt proposed a method called critical chain project management (CCPM) to minimize the inefficiencies identified in traditional project management. The project management community accepted the proposed method as a viable alternative. However, to allow its implementation with a multiproject system, more research was necessary. Seeking to identify the key factors that influence the performance of the multiproject system applying the CCPM method, we performed a case study. Logistic regression analysis showed that applying the CCPM method in a multiproject system allows for better time estimation of activities and facilitates the allocation of critical resources.

Production control in precast fabrication: considering demand variability in production schedules

2011 ◽  
Vol 38 (2) ◽  
pp. 191-199 ◽  
Author(s):  
Chien-Ho Ko
Keyword(s):  
Lead Time ◽  
Production Control ◽  
Time Estimation ◽  
Customer Behavior ◽  
Business Success ◽  
Lead Times ◽  
Estimation Model ◽  
Key Factor ◽  
Demand Variability ◽  
The Impact

On-time delivery is a key factor in the business success of precast fabricators. The greatest obstacle to achieving this goal is demand variability. The objective of this research is to develop a plan that continuously improves production control systems for precast fabrication. This plan involves a lead time estimation model (LTEM) and schedule adjustment principles. The LTEM is established to estimate the impact of demand variability. In the model, previous jobs are analyzed as indicators of customer behavior. Using the captured behavior, fabrication lead time can be estimated for forthcoming projects. Two principles are proposed to adjust the production schedule according to the estimated lead times. Two adjustment principles are designed to reduce the impact of demand variability: (1) start fabrication later relative to the required delivery dates and (2) shift production milestones backward to the end of the production process. The effectiveness of the developed improvement plan including LTEM and the adjustment principles were validated using a real precast fabricator. The proposed approach is one of the first studies to use historical data to estimate the impacts of demand variability based on customer behavior.

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