Information and Knowledge Management using ArcGIS ModelBuilder

Denisa Ferenčíková
2. Software tools for production planning and control support
Methods and software tools for production planning and control have been evolving for decades, but it
is only intense development in business informatics recently that has allowed them to be fully
integrated in the planning algorithms of ERP systems or other individual applications for supporting a
production process (Sodomka 2011). A primary distinguishing characteristic of the various planning
methods is the production control principle, i.e. a pull, push or combined system (Fig. 1).
PULL system
Combination
PUSH x
PULL
PUSH system
MRP I MRP II
JIT E-KANBAN
TOC
DBR OPT
APS MSO
SEIBA SRM
N
1960 1970 1980 1990 2000 2010
Figure 1: Evolution of planning methods (modified by Entrup 2005)
Years
One of the first methods to be supported by information systems was Production Control according to
a minimum inventory. This concept was later followed by methods such as MRP I (Material
Requirements Planning) and MRP II (Manufacturing Resource Planning), which are still frequently
used in practice (Sheikh 2003).
With a changing market environment and growing demands for flexible manufacturing systems,
standard push principles in production control are beginning to be dropped in many cases.
Information systems producers have also respected this trend and are integrating (in their
applications) methods based on pull principles. These are able to plan and manage production with
regard to the requirements of Lean manufacturing. Although the core principles of the JIT method
were formulated in Japan as long ago as the 1950s, they were transposed into information systems
some years later. They can be perceived from two perspectives. In a narrow sense, JIT focuses on
managing an internal production process and tries to achieve the output desired in the required time,
in prime quality and with zero stock. From a wider perspective, JIT aims to bring about the values of
production indicators mentioned above within the whole supply chain (Sledzinski 2004, Sodomka
2011). The most typical example of applying JIT in an information systems environment is Electronic
Kanban (eKanban).
In the late 1970s, when E. M. Goldratt presented his revolutionary Theory of Constraints (later
referred to as TOC), approaches to production planning began to alter. Most companies encounter
the issue that it proves challenging to uniquely determine whether it is better to use push or pull
principles in their production control process. In reality, it is often necessary to combine both
approaches and, therefore, information systems producers have introduced new solutions that
support this combination (Goldratt 2000, Sodomka 2011). Examples include a method for address
production called Seiban, and others based on the TOC philosophy such as APS (Advanced Planning
and Scheduling), DBR (Drum-Buffer-Rope) or OPT (Optimized Production Technology).
More recently, within the development of production planning systems, a typical feature has been a
transition from rigid planning algorithms to various dynamic systems with automated optimization of
the production process. One of the tools mentioned above is the concept of continuous simulation
and optimization known as MSO. Despite being one of the most advanced management methods, it is
not often integrated in ERP systems. The next dynamic approach in production planning and control
was presented in the late 1990s by German businessman Steffen Berghof. This involved the concept
of cybernetic self-regulatory mechanisms known as SRM. The primary task of SRM is to constantly
compare set goals with actual results then continually update and set up relevant parameters in order
to reach and maintain the value required (Ferenčíková 2010, Pavlas 2009, Sodomka 2011).
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