Abstract A large assembly plant of parts for the automotive industry uses an MRP system for the mid-term planning and has developed some finite-capacity scheduling software for the scheduling of the final assembly step of its products. This software uses a heuristic which tries to respect due dates and to minimise production costs, which consist mainly of set-ups. One of the problems with this software is that it does not take the availability of subparts into consideration. In fact, the production of subparts must also deal with the problem of set-up minimisation. The difficulty lies in the fact that the technical parameters that determine “a good sequence” differ for each production step. At the moment, human planners spend a lot of time and effort to coordinate and fine tune the production sequences in the various production and assembly steps. There are plans to produce some subparts of the product in a Kanban-controlled manner. A simulation model is described which allows to study the feasibility of these plans and to determine the operational parameters (such as number of Kanbans and container size). This feasibility study was carried out for two scenarios: 1. (1) all subpart types are produced in a Kanban controlled manner and 2. (2) only the production of fast-movers on two (out of three) machines is Kanban controlled. The sensitivy of the results vis-a-vis a number of assumptions (set-up time reduction, machine breakdowns, tool availability, etc.) is also presented.
[1]
Ahmet Satir,et al.
A kanban-based simulation study of a mixed model just-in-time manufacturing line
,
1995
.
[2]
N. Singh,et al.
Modelling and Analysis of Just‐in‐Time Manufacturing Systems: A Review
,
1992
.
[3]
U. Karmarkar.
Getting control of just-in-time.
,
1989,
Harvard business review.
[4]
Richard J. Schonberger.
Applications of Single-Card and Dual-Card Kanban
,
1983
.
[5]
Hiroshi Ohta,et al.
The optimal operation planning of a Kanban system with variable lead times
,
1994
.
[6]
Masaaki Imai,et al.
Kaizen (Ky'zen) : the key to Japan's competitive success / Masaaki Imai
,
1986
.
[7]
Steven Nahmias,et al.
Production and operations analysis
,
1992
.