1. INTRODUCTION:

Flexible Manufacturing system is a concept that is capable of meeting customized production requirements. The issues such as reduction in waiting time, market-response time to meet customer demand, productivity and flexibility are the primary goal of today‘s manufacturing Industry .These challenges can be addressed effectively bby fully integrated flexible manufacturing environments. A flexible manufacturing systems (FMS) is an integrated computer-controlled unit, a configuration which consists of a numerical control (NC) system with finite machine tools, auxiliary production equipment and a material handling system which is designed to create a manufacturing environment which is to manufacture a low to medium volumes of a mid wide variety of fine high quality products at low cost simultaneously. The dimensional flexibility is a feature, which provides hands-on flexibility in FMS, which can be characterized in no routing flexibility, flexible manufacturing machines, and operational sequences and with complete routing flexibility. These manufacturing systems have been designed to manufacture various part types efficiently with low to medium volume. It comprises of high levels of flexibility with the high productivity and low level of a work- in-process inventory, the want of quality for flexibility, and efficiency has imposed major change in manufacturing industries.

2. LITRATURE REVIEW:

An FMS is designed to manufacture a variety of items and to provide alternative processing routes for individual products. Shankar (1991) resolved the problem of the real time operation control by part entry selection[1]. Brown et al. (1984) introduced alternate routes includes the use of different machines to perform the same operation[2]. Ammos, (1985) resolve the real time operational control considering two objectives, namely balancing workload and minimizing work stations visits,[3] Bryne, (1997) The operational control in FMS with flexible alternative machines and flexible alternative operation sequences[4].Seda (2005) they introduced a real time methodology for minimizing mean flow time in FMSs with routing flexibility using threshold- based alternate routing[5].Veeranna. V, Dattatreyasarma. B, Chakraverti, G(2006), made an investigation on Optimization of FMS Layout by Heuristic Procedure with Scheduling as a Constraint [6]. N. Gopikrishna (2017), made a review on Flexible Manufacturing Systems which was explained in his International Journal “rational exploration of flexible manufacturing systems” [7]; Chintankumar R. Patel and Dusan N. Sormaz gave a description on an integrative methodology for simulation of FMS with Alternate Routings [8].

3. PROBLEM FORMULATION AND METHODOLOGY:

The objective of this study is to investigate how to optimize the manufacturing time by applying flexible routing control policies that influence the system performance which are under various operating conditions. This type of a flexibility leads to potential improvement in the system performance. Flexsim Simulation software is used in the present study to model and simulate FMS environment. Flexsim simulation modeling software is useful to analyze complex systems. The simulation software flexsim helps to develop a simulation model for solving the purpose of understanding how the behavior of the system and to explore the impact of routing flexibility.

Flexsim provides an integrated framework for designing and modeling simulation models in a wide variety of applications. The modeling system (software – Flexsim), is a powerful and flexible tool that allows designers and analysts to create running animated simulation models that accurately represents a system. Software flexsim employs an object-oriented design for complete and entirely a graphical model development. In flexsim, the user builds an experimental model by placing modules (boxes of different shapes) that represent processes or logic, connector lines to join these modules together specifying the flow of entities. Statistical data, such as cycle time and WIP (work in process) levels, can be recorded and output as reports. Simulation analysts place graphical objects, called modules, on a layout in order to define system components such as machines, operators, and material handling devices.

3.1 Simulation Model:

Basically in simulation model wide variety of objects have been introduced to fulfill objectives of manufacturing systems here for practical application we assumed 4 machines with 6 different operations to minimize waiting time to meet customer demand, enhance flexibility and optimize manufacturing time.

Fig. 1: Basic FMS Layout (on Flexsim)

The four machines considered as per sketch made shown in fig-1 processing with three part types undergoing six various operations O1, O₂…O6 have been chosen with assumptions made by the system as following:

3.2 System assumptions:

1. One machine does only one job at once.

2. Machines are alternative with one another.

3. One machine only can be down at a time

4. Operational sequences for a part is fixed for a particular job type.

5 Machining sequences for a job is fixed for a particular part type.

6. Machines were arranged at equal distances.

7. Part processing time is normally distributed.

8. Set up time is not sequence dependent.

9. Sufficient amount of tools are available for tooling.

3.3 Routing strategies:

The principle of routing flexibility as given in the table.1, exists the remaining operation for a part which is to be operated can perform in any order and the next operation that to be selected can perform on any one of the alternative machines. During no loading simply Job Flows from Source to M1, M1 to M2, M2 – M3, M3 to M4, then M4 to Sink as shown in figure 2. Table 2 entails the job machining time specicifed during machining process and processes.

Fig 2: JOB Flow During NO Loading

Table 1:

JOBS	Machining Process 1	Machining Process 2	Machining Process 3	Machining Process 4	Machining Process 5	Machining Process 6
Job Type I	M1,M3	M2,M3	-	M4,M2	M4,M1	-
Job Type II	M1,M3	M2,M3	M3,M1	-	M4,M1	-
Job Type III	-	M2,M3	-	M4,M2	M4,M1	M4,M2

Table 2:

JOBS	Processing Time on Machine For Process 1	Processing Time on Machine For Process 2	Processing Time on Machine For Process 3	Processing Time on Machine For Process 4	Processing Time on Machine For Process 5	Processing Time on Machine For Process 6
Job Type I	1[5],3[7]	2[7],3[9]	-	4[13],2[16]	4[9],1[10]	-
Job Type II	1[5],3[7]	2[7],3[9]	3[11],1[15]	-	4[9],1[10]	-
Job Type III	-	2[7],3[9]	-	4[13],2[16]	4[9],1[10]	4[11],2[13]

3.4 SIMULATION RESULT:

The expected layout using flexsim have been depicted in figure 3. In order to investigate machine utilization, reduced the waiting time, mean flow time & significant impact of various factors in the system performance For 100 parts, we developed a simulation model, which is flowing through a loop conveyor by set routes that utilizing complete routing flexibility that has been compiled and made to run.

Fig 3: Expected Simulation Layout (During Loading) on FLEXSIM

Graph 1: Machine utilization Graph 2: Time utilization

During simulation process, utilization of machine 1 is more and machines 3, 4 with slight variation which is shown in graph 1.Time utilization, from various Job Types I, II and III; M I found to be maximum with processing time and M 4 was seemed to be minmum.Utilization of M 3, M 4 are equal in idle time and found to be with NO Block time, that are have been depicted in graph 2.

Graph 3: Part staytime Graph 4: Work and Time Histogram

Waiting time of the jobs during maching, one that can be seen in the graph 3. From the graph 4, it can be seen that there is a slight shortfall workinprogress with TimeInSystem at 200 cycles which is found to be maximum whereas low progress was seemed at 350 cycles. Below given Table 3, describes the simulatin analysis

Table 3: Simulation State Analysis

State analysis
	Total	Processing	Releasing	Setup	Idle	Blocked	Empty
Queue3	99.3%	0.0%	99.3%	0.0%	0.0%	0.0%	0.7%
M1	99.8%	49.8%	0.0%	49.9%	0.2%	0.0%	0.0%
M2	66.1%	43.3%	0.0%	22.8%	25.8%	8.1%	0.0%
M3	66.2%	50.8%	0.0%	15.5%	33.8%	0.0%	0.0%
M4	56.4%	39.4%	0.0%	17.0%	34.4%	9.2%	0.0%

4. CONCLUSION:

Simulation study is carried out to investigate number of part types, Total Machining time, Machine utilization, and various part flow time. In this paper complete routing flexibility with machine change and alternate machining process and processes have been introduced. The various factors that include complete routing flexibility with machines, their changes and sequences. Flexsim simulation software has been introduced to perform the system analysis. It can be seen from the results of a simulation state analysis that was proposed for job type 3 which is having minimum of total machining time and maximum of idle time while for part type 1 it is minimum.

5. REFERENCES:

1. A K Sethi and S P Sethi (1990), Flexibility in manufacturing: a survey, Int. J. Flexible manufacturing systems 2, pp. 289-328.

2. J Browne, D Dubois, K Rathmill, S Sethi and K Stecke (1984), Classification of flexible manufacturing systems, The FMS Magazine, April, pp. 114-117.

3. J C Ammons , C B Lofgren and L F McGinnis (1985), A large scale machine loading problem in flexible assembly, Annals of Operations Research, 3, pp. 319-322.

4. M D Bryne and P Chutima (1997), Real-time operational control of an FMS with full routing flexibility, International Journal of Production Economics 51, 1-2, pp. 109-113. [

5. Seda Ozmutlu and Catherine M Harmonosky (2005), A real- time methodology for minimizing mean flow time in FMSs with routing flexibility: Threshold-based alternate routing, European Journal of Operational Research, pp. 369-384.

6. Veeranna. V, Dattatreyasarma. B, Chakraverti. G(2006), Optimization of FMS Layout by Heuristic Procedure with Scheduling as a Constraint”Industrial Engg.Journal, 25-28

7. N. Gopikrishna “rational exploration of flexible manufacturing systems” - International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 – Vol – 03, ISSUE – 12, Dec, 2016.

8. Chintankumar R. Patel and Dusan N. Sormaz “An Integrative Methodology for simulation of FMS with Alternate Routings” – International Journal of Engineering and management (IJIEM), Vol. 3 No 3, 2012, pp. 153-161.

Received on 13.10.2017 Accepted on 10.11.2017

Research J. Engineering and Tech. 2018;9(1): 85-89

DOI: 10.5958/2321-581X.2018.00013.2