Effectiveness of JIT Production System among Employees Working in Electrical Industry during Pre-Pandemic Situation at Chennai

2020 ◽  
Vol 33 (02) ◽  
Author(s):  
Dr. P SUNDHARESALINGAM ◽  
Keyword(s):  
Production System ◽  
Electrical Industry ◽  
Jit Production

Optimal numbers of two kinds of kanbans in a JIT production system

1995 ◽  
Vol 33 (5) ◽  
pp. 1387-1401 ◽  
Author(s):  
K. OHNO ◽  
K. NAKASHIMA ◽  
M. KOJIMA
Keyword(s):  
Production System ◽  
Jit Production

Optimal dispatching control of an AGV in a JIT production system

2002 ◽  
Vol 13 (8) ◽  
pp. 746-753 ◽  
Author(s):  
Syuhei Hirao ◽  
Mitsushi Tamaki ◽  
Katsuhisa Ohno
Keyword(s):  
Production System ◽  
Jit Production ◽  
Dispatching Control

A solution approach to a synchronisation problem in a JIT production system

2013 ◽  
Vol 25 (12) ◽  
pp. 990-998 ◽  
Author(s):  
Emin Gundogar ◽  
Aysegul Yilmaz ◽  
Burak Erkayman
Keyword(s):  
Production System ◽  
Solution Approach ◽  
Jit Production

Just-In Time Production System Using Fuzzy Logic Approach and a Simulation Application

2012 ◽  
Vol 445 ◽  
pp. 1029-1034 ◽  
Author(s):  
Yavuz Ozdemir ◽  
Pelin Alcan ◽  
Huseyin Basligil ◽  
Cagri Dokuz
Keyword(s):  
Fuzzy Logic ◽  
Production System ◽  
Production Systems ◽  
Low Cost ◽  
Production Method ◽  
Transformation Process ◽  
Just In Time ◽  
Time Production ◽  
Fuzzy Logic Approach ◽  
Jit Production

While firms are operating in a global competitive environment, they are subjected to changes because of the increased competitiveness and developed technologies. Therefore, this transformation process forces to produce with just-in-time production and low cost products or services and leads to customer satisfaction. Until today, competitive conditions, efficiency, productivity and quality of production, forced the firms to put more emphasis on production systems. Therefore, the firms are more interested in scientific analysis, planning and controlling of their production systems. As a result, one of the newest approaches is Just in Time (JIT) production system which emerged after WWII in Japan and aims to decrease the inventory cost and maximize the quality. The philosophy of this approach is to produce the necessary amount of production, when and where needed at the required quality.But JIT production system is weak in unclear species. For this purpose, the general and necessary solution is using fuzzy logic. In this paper we discussed about the simulation of an assembly line with 3 steps; firstly using Kanban production method, secondly non-using Kanban production method, and lastly using Kanban production method with fuzzy times. And also the comparisons of these steps will also be studied in this paper.

scholarly journals A Dynamic Scheduling Method for Painting Process with JIT Production System

2000 ◽  
Vol 13 (2) ◽  
pp. 65-71
Author(s):  
Jae Kyu Yoo ◽  
Masafumi NOGUCHI ◽  
Itsuo HATONO ◽  
Shinji TOMIYAMA ◽  
Hiroyuki TAMURA
Keyword(s):  
Production System ◽  
Dynamic Scheduling ◽  
Scheduling Method ◽  
Jit Production ◽  
Painting Process

The Effect of Optimum Number of Kanbans in just in Time Production System to Manufacturing Performance

2013 ◽  
Vol 315 ◽  
pp. 645-649
Author(s):  
Ahmad Adnan Naufal ◽  
Ahmed Jaffar ◽  
Yusoff Noriah ◽  
Nurul Hayati Abdul Halim
Keyword(s):  
Mathematical Model ◽  
Production System ◽  
Material Flow ◽  
Just In Time ◽  
Optimum Number ◽  
Relevant Parameter ◽  
Stock Level ◽  
Time Production ◽  
Manufacturing Performance ◽  
Jit Production

This paper discusses a method to determine optimum numbers of kanban in Just In Time production system and analyzes effect of optimum numbers of kanban to manufacturing performance. Method to determine kanban numbers was carried out by designing kanban flow based current situation, gathering relevant parameter on floor and company database, and calculating of kanban quantity through basic mathematical model. The basic mathematical model of kanban is derived according to designated kanban flow in JIT production system. The optimum number of kanbans would control and regulate material flow in manufacturing, thus JIT is achieved. As a result, product lead time and inventory stock level are improved. The conclusion is that an appropriate determination numbers of kanban could lead to optimizing manufacturing capability.

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