Teoria Industrial Technologies

A B C D E F

of course I’m able to balance a line only if I can distribute tasks on different stations in the right way

(maintaining the right sequence!)!

In this case I can’t have a perfect balanced line: A B,C,D E,F

4’ 3’ 5’

Strengths:

Simple production management: transfer line is a series of machine, by definition, which are visiting according

to a specified sequence (depending on the technological requirements of a product), so we don’t have any

alternative routings, and the management it’s simple because it doesn’t require any decision making. When

we have a product we have only to decide the length of the production campaign. According to the Magee

Boodman’s method we can identify the optimum number of campaigns (respect to costs of setup and

inventory primarly) that have to be produced in the year, so we can calculate the best batches size as BS =

j

D /N (annual demand of j / optimum number). Of course if we have more than one product to manufacture

j opt

(multi-model case) we have also to decide the best batches sequence (basing on the setup time, because

some setup times can depend also on the sequence):

Production management Single-model Multi-model

Batch sizing X X

Batch sequencing X

High machine utilization: the line is supposed to work every time there’s a production campaign, and the

demand of the product is high and stable. This stability in the production mix makes the problem of balancing

easier

Low space occupied: this is a compact system, so the space occupation comes from the stations and the

material handling systems installed (if I have a synchronous transfer line, in other case I have also to provide

a space for the buffer).

These strengths lead us to have:

Low WIP,

Low lead-time (also considering variability) because of the absence of queues in the synchronous, but I have

also low LT in the asynchronous transfer line.

Low need for workforce: there are few tasks that are auxiliary, because basically this is an automatic system,

Qualitative characteristics of products are stable: there is only one technological routing, and I have quick

feedbacks.

Weaknesses: 

Low flexibility: mix flexibility we are basing the sequences of the operations (and of course also the layout

and the order in which machines are installed) according to the specific technological routing required by the

products. Each line can manufacture only few products (in the same family).

Product flexibility is low because I don’t have alternative routings, so, if I want to produce pre-series, I have

to stop the normal production.



Expansion flexibility (deals with the introduction of new capacity or new technological capabilities in the

system) low due to space problems.

Variation in volumes (volume flexibility) can be a concern both if the volumes are increasing or decreasing,

High investment needed: being an automated system we have a lot of fix costs to bear,

Long time required to start new productions: change from a product type for the one the line was dedicated

to another one, and this means that I have also to change the technological routing,

High risk of obsolescence: the facility lifetime is strictly bound with the product lifetime, so if the product

becomes obsolete, also the line will be obsolete (not the machine, because we can use them for other

productions)

Significant impact of failures: if only one machine (or other devices) has broken down, the entire line will

have to stop until that machine is totally repaired. Buffers can protect us for a while, or I can think of installing

more parallel machines (e.g.: two machines are needed but I decide to install three machines, so, if one of

them has failed, I have another machine to manufacture my production), but, of course, this will arise more

costs.

Rough design of a synchronous transfer line (single-model):

1. Define the technological routing and operations of the product

2. Identify all the machine types that are needed and balance the line. I have to make a distinction

between: Specialized dedicated machines General purpose machines

#operations Low High

Speed High Low

performance These machines are useful to fulfill a These machines are useful to fulfill a

strategy focused on efficiency strategy focused on flexibility

3. Calculate the theoretical production capacity:

TPC= 3600 / CT [p/h]

where

CT = cycle time of the line [seconds/piece]

Of course if we rebalance the line we may have a different TPC because I may have a different cycle

time.

4. Calculate the actual production capacity

APC = TPC * A * (1 – SR) [p/h]

where

A = line availability (0 < A ≤ 1). Availability can be defined as a percentage of time coming from

this calculus: A = uptime / (plant uptime + downtime)

SR = scrap rate (0 < SR ≤ 1)

We don’t have HC because these lines are highly automated.

5. Compare the actual production capacity and the demand. If necessary, modify the line as it follows:

a. go back to step 2 rebalancing the line,

b. add new machines,

c. increase the availability,

d. put in parallel more machines so I can create different routings on which I can produce

different parts. In this case I have to split the time of production of one machine type on the

different products (type) I can produce in parallel on this machine! (e.g.: if two products are

produced in parallel on a machine type that consumes 7’, I have a cycle time of 7’/2

products!).

Rough design of a synchronous transfer line (multi-model):

Assumptions:

Pieces are manufactured in batches (batch A, batch B, batch C and so on); changing production from

- one batch to another requires a setup,

Setup times do not depend on the production (batch) sequence or we assume that we’ve already

- found the optimal sequence.

1. Identify the production mix

2. Define the technological routing and operations of the products (in the production mix)

3. Identify all the machine types that are needed and balance the line (for each product)

4. Calculate the cycle time for each product j

CT = max {TL } [seconds/piece]

j h jh

where

TL = unit working time of product j at workstation h [seconds/piece]

jh

5. Calculate the whole time to produce a batch of product j

T = CT * H + CT * (Q -1)+ STT [seconds/batch]

j j j j j

where

H = number of workstations in the line

Qj = batch quantity of product j [pieces/batch]

STT = setup time related to a batch of product j [seconds/batch]

j

Approximating:

6. Calculate the time needed for a set of batches (within a production campaign)

j=1N

T = ∑ Tj [seconds/batches]

where

N = number of batches (one batch per product j in the campaign)

7. Calculate the average theoretical production capacity

j=1N

TPC = 3600 * ∑ Qj / T [p/h]

8. Calculate the actual production capacity

APC = TPC * A * (1 – SR) [p/h]

where

A = line availability (0 < A ≤ 1)

SR = scrap rate (0 < SR ≤ 1)

9. Compare the actual production capacity and the demand. If necessary, modify the line and go back

to step 3 and intervene in one of the following:

 Reduce scrap ratio

 Reduce breakdowns’ frequency

 Decrease the time required to restore the functioning of the station after a fault

 Modify the configuration of the transfer, by choosing different machines and/or increasing

the number of machines in series and/or adding machines in parallel in some stations.

Obviously, it need to balance workload again.

MACHINE INTERFERENCE

We analyze this problem under the workers’ perspective.

In manufacturing systems, a worker is usually required to attend two or more machines (similar or different

machine types) running concurrently, being the system configured as a job shop or others. Machine

interference occurs when the worker is requested a task while being already busy in another task, that can

be expected (regular) or not (i.e. attending another machine, unloading other pieces from another machines,

do some maintenance, and so on. Ex: we may have a material out of the tolerance limits, and it blocks the

machine, so the operator has to remove it!)

The measure of this problem is the interference time (i.e. the time the other machines have to wait until the

worker has completed his current task).

Problems:

 How many operators do we need to attend machines? We need to decide the assignment of workers

on machines/workstations/…!

 Where are the bottlenecks (the resources that are limiting capacity): machines or operators? Waiting

means that we’re losing production capacity: if workers are doing other tasks is the machine that is

waiting, but we consider the machines as a bottleneck, due to their high cost, so, in this case, is the

operator that is waiting for the machine. In conclusion we have to find a good balance between

workers and machines in order to limit the interference time.

To solve the problems above we have to:

 analyze machines’ and workers’ operating cycles;

 evaluate the impact of the interference times on the machines’ capacity (i.e. the required capacity

to meet the demand).

When studying the machine interference, it is worth devising the utilization of both workers and machines

during their operating cycles.

This can be obtained by adopting simple graphical methods, e.g. a Gantt chart (that is showing us, using bars

and lines, the scheduling of the machines. A bar’s length is representative of the real time consumed by an

operation).

If I suppose that the time when the worker is required (a single red bar) is 2, and the time when the worker

is not required (a single yellow box) is 10, I have a window of 10 in which the operator can working on other

machines. In conclusion, a single operator, according to this example, can work on 12/2=6 machines! In this

example the utilization rate of the worker is 50%.

Of course there could be differences between a machine and another! 2 may be considered as an average.

In this case, the worker is required to attend the machine in order to load/unload work-pieces and to fix

minor problems.

The total interference time is the sum of all the interference times on the three machines.

The utilization rate of the worker, in this case, is high (66% = (red+blue lines) / total production time).

1.33 is the average time loss per machine (sum of green lines / number of machines).

The Gantt method is really useful for a qualitative reasoning (it provides a rough analysis of the current

scenario), but an analytical method is required in order to better solve the problem!

Performance evaluation – state space method

It’s an approximated method, and it can be easily performed on Excel.

It is based on the following general assumptions:

 the state of the system depends on the state reached by its machines;

o the state of the system as function of the state of its machines, because a machine issues a

service request, the workers deliver the s