ADVANCED PRODUCTION SCHEDULING APPLIED TO DIFERENT LEVELS OF MASS
CUSTOMIZATION INDUSTRIAL ENVIRONMENTS
Author: Felipe Corrêa de Oliveira
Supervisors: Paulo Martins, Co-Supervisor: Dinis Carvalho
University of Minho
School of Engineering
Production & Systems Department
[email protected]
Conclusions
Introduction
After the growth and development of the Mass Production, the Mass
Customization raised as a new trend on the industrial scene.
Nowadays the organizations pursuit to deliver a big volume of
customized products being profitable on their daily operations. Mass
customization relates to the ability to provide individually designed
products and services to every customer through high process
flexibility and integration (Pine 1999).
According to this new industrial environment, there are a lot of abilities
and critical factors that helps companies on achieving this objectives.
Depending on the level of mass customization they are offering, from
standardized products (Mass Production) to totally customized
products (Mass Customization), companies are implementing a lot of
actions to be flexible and profitable. The Mass Customization System
consists on the group of process and methodologies that supports a
successful Mass Customization Strategy Implementation.
One of the main actions to be implemented, Agile Manufacturing
supported by an efficient Production Scheduling Model becames an
important enabler for Mass Customization success.
Mass Customization and Production SchedulingSystems
After the recent bibliography investigation, the researcher concluded
that:
• Most of the Scheduling Models only supports specific industrial
environments and conditions;
•Most of the previews researches was under specific industrial
environment conditions;
•And finally, the development of a flexible scheduling model definition
methodology, able to be applied on every production environment,
was not described before.
With this assumptions a simulation and testing model was conducted
to develop and evaluate this method (Figure 1).
Environment
Production
Strategy
Market
Product
Results
Scheduling Model
Production
Process
Analysis
Optimized Model
Industry
Condictions
Yes
OK?
Research Agenda
In order to develop a new flexible Production Planning System to deal
with different levels of Mass Customization and different Industrial
environments, first the author had to focus on investigating all the
current production planning models actually available. Models like
MRP (Plenert, 1999), Kanban (Jodlbauer & Huber, 2007), ConWip
(Spearman & Hoop, 1991), DBR (Goldratt, 1990) and POLCA (Suri,
2002) were strongly analized to determinate how they behave
submitted to different levels of Mass Customization and different
combinations of market conditions, production process and product
characteristics.
The success of mass customization appears to be dependent on a
flexible production system which depends on a flexible productions
scheduling model also. Today the adoption of a model like this
emerges as one of the success enablers for the mass customization
strategy and on the other hand the other models are limited and
unflexible.
References
No
Mass Customization consists on deliver high customized products on
high scale, with low cost and efficiency. Some authors describes more
than one level of Mass Customization. These levels can be
determined by the combination between Market Conditions,
Production Process and Product Characteristics . The need to
develop agile production systems and the actual technology available
enforces the rapid Production Planning Systems evolution.
According to the research development described on the previous
sections is possible to have an idea about this innovative method
proposed. Moreover, it is unquestionable the importance and
usefulness of the proposed method to the success of companies in
the search for an agile manufacturing system.
Figure 1:Research Method
This method consists on: First determine different industrial
environments according to the possible combinations across market
conditions, product characteristics and production process; second
determine a Scheduling Model based on Fernandes (2007)
dimensions of Production Scheduling models, named in his research
as Work Load Control mechanism; third simulate the scenario using a
simulation model develop by Melnyk & Ragatz (1989) and evaluate
the results based on common production analysis metrics; and fourth,
repeat this third step until achieve an optimal model.
Research Status
Now the author is facing the fourth step, trying to achieve an optimal
model for each environment and developing a method to make this
model specification automatic.
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em
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de
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e
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