Manufacturing processes

05/03/2023 Assembly Systems 1

Chapter 2 – Manufacturing Operations

John L. Evans, Ph.D.INSY 4700


Introduction to Assembly Systems

• Definition of the term assembly– The aggregation of all processes by which various parts and sub-

assemblies are built together to form a complete, geometrically designed assembly or product either by an individual, batch, or continuous process.

• Assembly of manufactured goods accounts for:– over 50% of total production time, – 20% of the total unit production cost, and– 33%-50% of labor costs


Types of Manufacturing Industries

• Aerospace Apparel Automotive• Basic Metals Beverages Building Materials• Chemicals Computers Construction• Appliances Electronics Equipment• Fab Metals Food Glass• Machinery Paper Petroleum• Pharmaceuticals Plastics Power Utilities• Publishing Textiles Tire and Rubber• Wood Furniture


Processing and Assembly Operations

• Solidification Processes– Casting and Molding

• Particulate Processing– Pressing Powers and Sintering

• Deformation Processes– Forging, Extrusion, Rolling, Drawing, Forming, Bending

• Material Removal– Turning, Drilling, Milling, Gringing

• Material Finishing– Heat Treatment, Cleaning, Surface Treatment

• Assembly Operations– Welding, Brazing, Soldering, Adhesive, Rivets, Press, Threaded Fastners


Product Assembly

• Virtually all end products go through some assembly process.

• Approaches– Craftsman approach

l

Output = l parts/unit time


Product Assembly


• Approaches– Craftsman approach

l l l

Output = 3l parts/unit time


Product Assembly


• Approaches– Craftsman approach– Assembly line

l l l

3l

3l

3lOutput = 3l parts/unit time

Output = 3l parts/unit

time


Example

l l l

3l

3l

3l

l = 2 part/hour (each)

3l = 6 parts/hour

m = 1/l = 1/2 hour

l = 2 parts/hour

3l = 6 parts/hour (each)

n = 1/3l = 1/6 hour

m1

n3

m3

n2

n1

m2

Assume m1=m2=m3=m Assume n1=n2=n3=n


Assembly Line

• Each part moves sequentially down the line, visiting each workstation.

• Assembly (or inspection) tasks are performed at each station. 1

2

3

4

5

6

• Tc is defined as the cycle time. At steady state, one unit is produced every Tc time units (i.e., TC = 1/required number of assemblies per unit time).

• Paced lines vs. unpaced lines• Single product vs. mixed lines• Flexible flow lines


Assembly Line Balancing

• Assembly line balancing problems:– ALB-1 - Assign tasks to the minimum number of stations such that

the workload assigned to each station does not exceed the cycle time, TC.

– ALB-2 - Assign tasks to a fixed number of stations such that the cycle time, TC, is minimized.

• An assembly consists of a set of tasks. • Task precedence relationships

– Precedence relationships are described by a graph G = (N, A) where njÎN represents task j, and aijÎA indicates that task i is an immediate predecessor of task j.


Production Concepts and Models

• Production RatesTC= TO + Th + Tth

Where TC = Operation Cycle Time TO = Time of Actual Processing Th = Handling Time Tth = Tool Handling Time

For total batch processing time

Tb = Tsu + QTc

Where Q = Batch Quantity Tsu = Total Setup Time


Production Concepts and Models (2)

The Average Production Time for a Part (Batch)Tp = Tb/Q

The Average Production Rate (pc/hr)Rp = 60/Tp

For Job Shop Production Tp= Tsu + Tc

For Mass Production – Q is very large making Rp ~ = Rc = 60/Tc

Where Rc =Operation Rate of the Machine



• For Multiple Stations Dividing work evenly is not realistic• Bottleneck Station is the “Gating” or limiting operation

Tc = Tr + Max To

Where Tr = time to transfer work between stations Max To = operation time at bottleneck operation

Therefore the theoretical production rate is approximatelyRc = 60/Tc



• Production Capacity is defined asPC = nSHRp

Where n = number of work stations S = number of shifts per period H = hr/shift Rp= hourly production rate of each center • Utilization is defined as U = Q/PC• Availability is defined as

A = (MTBF – MTTR)/MTBFWhere MTBF is mean time between failure (hr)

MTTR is mean time to repair (hr)


Manufacturing Lead Time

• The Lead Time for Manufacturing a Product Through the Entire Operation is defined as

MLTj = Sum of (Tsuij + QiTcji + Tnoji) i = 1 to oj

Where Tsuji = Setup Time for Operation i Qj = Quantity of product j Tcji = Operation cycle time for operation i Tnoji = Nonoperation time with operation i


Manufacturing Lead Time

• Lead Time for Job Shop – Q = 1

MLT = no(Tsu + Tc + Tno)

• Lead Time in Mass Production

MLT = no(Tr + Max To) = noTc


Work-in-Process

• Work-in-Process is the quantity of products currently in the process of production

• WIP = [ AU(PC)(MLT)] / SH

Where A is Availability U is Utilization

PC is Production Capacity MLT is Manufacturing Lead Time S is number of Shifts per Week H is the number of Hours per Shift


Costs of Manufacturing

• Fixed and Variable Costs

TC = FC + VC (Q)

Where TC is the Total Cost FC is the Total Fixed Cost VC is the Variable Cost per unit Q is the Quantity


Manufacturing Analysis

• Evaluate or Optimize– Minimize Throughput Time– Minimize Labor– Minimize Capital Investment– Maximize Capacity– Minimize Operational Cost– Minimize Cost Per Unit


Types of Analysis Problems

• Capacity of Process Time• Analyze Lead Time to Production• “Optimize” Process Steps or Sequence• Evaluate WIP • Evaluate Cost of Operation• “Optimize” Capital Investment• Minimize Travel Time• Minimize Floorspace


Example Problem

Task ti Predecessorsa 3 -b 2 -c 3 a,bd 2 ae 1 d

a

b

c

d e


Assembly Line Balancing

• Problem (ALB-1): Assign tasks to workstations• Objective: Minimize assembly cost

– f(labor cost while performing tasks, idle time cost)• Constraints:

– Total time for all tasks assigned to a workstation can not exceed C. – Precedence constraints between individual tasks.– Zoning constraints

• Same workstation• Different workstation


Parameters / Inputs

• Parameters / Inputs– P parts/unit time are required – m parallel lines are to be designed (usually 1)– C = m/P is the required cycle time– ti is the assembly time required by task i, i = 1,…,N– IP = {(u,v) | task u must precede task v}– ZS = {(u,v) | tasks u and v must be assigned to the same

workstation}– ZD = {(u,v) | tasks u and v can not be assigned to the same

workstation}– S(i) is the set of successors for task i.


Parameters / Decision Variables (cont.)

• Decision Variables– k is the number of workstations required (unknown).

–

• cik is a set of cost coefficients such that:

• cik is the cost of assigning task i to station k

otherwise ,0

station toassigned is task if ,1 kixik

1,,2,1,1, nkcNc kiik


Problem Formulation

min c xik ikk

K

i

N

11

t x C k ki iki

N

, , ,1

1

x i Nikk

K

1

1 1, , ,

x x h K u vvh ujj

h

Î

1

1, , , ; ( , ) and IP

x x u vuk vkk

K

Î

1

1, ( , ) ZS

x x k K u vuk vk Î1 1, , , ; ( , ) and ZD

x i kik Î ( , ) ,0 1


Solving the Problem

• Very difficult to solve optimally– Integer variables– Non-linear constraints

• Heuristic Solutions– COMSOAL– Ranked positional weight

• Enumeration Methods– Tree Generation

• Niave approach• Fathoming rules


Example Problem

j tj Pj

1 5 -2 35 13 25 14 60 25 30 26 10 2,37 60 68 25 4,59 35 810 70 7,911 30 10

101

2

3

9

7

5

4

6

8

11


Example Problem (cont.)

j tj Pj All Predecessors1 5 - -2 35 1 13 25 1 14 60 2 1,25 30 2 1,26 10 2,3 1,2,37 60 6 1,2,3,68 25 4,5 1,2,4,59 35 8 1,2,4,5,810 70 7,9 1,2,3,4,5,6,7,8,911 30 10 1,2,3,4,5,6,7,8,9,10

101

2

3

9

7

5

4

6

8

11


Ranked Positional Weight Example

j tj Pj All Predecessors S(j) PW(j) Rank Station1 5 - - 2,3,4,5,6,7,8,9,10,11 385 1 12 35 1 1 4,5,6,7,8,9,10,11 355 2 13 25 1 1 6,7,10,11 195 4 14 60 2 1,2 8,9,10,11 220 3 25 30 2 1,2 8,9,10,11 190 5 36 10 2,3 1,2,3 7,10,11 170 6 27 60 6 1,2,3,6 10,11 160 7 48 25 4,5 1,2,4,5 9,10,11 160 8 39 35 8 1,2,4,5,8 10,11 135 9 510 70 7,9 1,2,3,4,5,6,7,8,9 11 100 10 611 30 10 1,2,3,4,5,6,7,8,9,10 - 30 11 7

C = 72

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Manufacturing processes