Appunti sulle lezioni del corso di Production Management - Secondo Parziale

II PARZIALE PRODUCTION

INVENTORY SYSTEM FOR DEPENDENT DEMAND (Slide 3-MRP Model)

Dependent Demand: is caused by something calculated according to the independent demand.

Is a demand originated within the Supply chain.

Overall View (Taxonomy)

Push System Dependent Demand

(needs based)

(requirements based)

Planning

Systems Traditional (EOQ model)

Pull System Independent Demand

(Stock based) Just In Time (JIT)

PULL vs. PUSH

When we talk about Requirements =>

we talk about Dependent demand,

which is originated within Supply Chain.

Multi-echelon supply chain

CODP = Customer Order Decuple Point

DLT here it means the time out customers

are willing to wait before receiving the cor-

responding product.

Seen in the eyes of the customer

MLT/SLT is the lead time in the eyes of the

supplier, and it measure how many hours/

days does it takes to let the corresponding product from the point of origins to the final customer.

How we can understand the differences between Pull and Push?

The upstream part of Supply Chain where we have plans, is named PUSH.

The downstream part of Supply Chain where we have orders/customer orders, is named PULL.

PUSH and PULL systems have nothing to do with finished product and component, not related to Demand vs Supply.

PUSH SYSTEM= materials (flow of good) PUSHED along the Supply Chain, according to a plan/forecast.

The one traditionally carried out upstream. (Dependent Demand)

PULL SYSTEM= materials (flow of good) PULLED along the Supply Chain, triggered according to a customer orders.

The one traditionally carried out downstream. The system is pulled by the market. I don’t do anything until I have a

demand from the market. (Independent Demand)

The planning of requirements consists of the determination of:

- WHAT

- HOW MUCH

- WHEN

to order at every stage of the production process.

We have already encountered these questions for (A*) and (B*) but here (C*) for the Push planning, the main differen-

ce is that we are talking about EACH STAGE of PRODUCTION. Instead for MPS and EOQ we talk about finished

products.

A. *MPS/ Aggregate planning —> with respect of finished product according to the typical representation of the cycle.

B. *EOQ —> Typical model is server/supplier.

Here: What produce, How much sent to warehouse, When. (one stage production system)

C. *Push Planning: Very meaningful difference. ALL THE LEVEL. Every stage of the production process.

In the Push Planning: we are expected to be able to convert a plan here, at the finished product level,

into a corresponding plan at the lower level. BOM= Bill of Material

DEPENDENT DEMAND: Planning at all the stages of the Supply Chain

(all the levels of the BOM)

MAIN CHARACTERISTICS OF PULL (STOCK BASED) SYSTEM

Objective: Having always the required product stored in the warehouse

(according to the service level).

we have to consider the warehouse immediately downstream.

Required Information: order issuing criteria (re-order policy) ROP

ex. the triggering mechanism

Reordering Point (ROP) usually EOQ

Objective Level (OL)

Implicit hypotheses:

- -

Smoothed and even stock consumption Saw tooth profile over time

- -

Independent demands among finished products Safety stocks based on variance

- -

Reduced demand variance Service level taken from the Gauss function

Distinctive features:

each phase of the production process

only “sees” the warehouse immediately down- This does not protect the inventory system

stream and it is completely blind with reference to bullwhip effect

against the so‐called

the remainder of the supply chain.

MASSIVE DISRUPTION: BULLWHIP EFFECT. S M D Mar-

BULLWHIP EFFECT: colpo di frusta. Source Distribution

Manufacture

Stage

A NOTE ON THE BULLWHIP EFFECT (1961, Forrester)

A very significant AMPLIFICATION effect.

Even a very small change at the finished product level (end customer) may represent a remarkable source of va-

riance (amplification) when going upstream along the supply chain and/or along the bill of materials.

1st effect of bullwhip is AMPLIFICATION.

Demand variance (y) and Years (x)

D: The distribution stage is almost the same along time,

(blue line) is subject to variance but this variance is limited

(almost 10%) .

a small change in demand causes a huge amplification

in suppliers stage. Example of cyclical variance.

2nd effect of bullwhip is a GAP effect.

Case1. Focus on 65-71:

We have a peak (increase) in the finished product stage: blue line. However in the same period the supplier line (red

line) is in a valley. A peak in D stage correspond to a valley in the S stage. You have a peak of demand and no stock

—> this can generate a huge stockout.

—> MASSIVE STOCKOUT (not able to sell product because we do not have components)

Peak in the Distribution stage and valley in the suppliers stage —> STOCKOUT

•

STOCKOUT: is much more expensive than overstock if we talking about specific company.

But here (grafico), we are talking about the WHOLE INDUSTRY (in US over 30 years). If we don’t have enough materials

in the whole industry, the customer will wait.

No one is able to “steal” our customer —> so in this case STOCKOUT is better than OVERSTOCK.

Case2. Focus on 74-78: Is exactly the opposite. Finished Product in a valley and Raw Materials in a peak.

—> EXCESS OF SUPPLY OF GOODS= ESG this lead to a MASSIVE OVERSTOCK

If a valley in the distribution stage happens —> OVERSTOCK

•

OVERSTOCK too much products, no one is buying them.

ESG= overstock at the macro level (Excess of Supply of Goods)

This is a problem because there is an imbalance between Demand and Supply.

=> as a CONSEQUENCE: we have a decrease in price, and in the LONG TERM we have LOSSES and BANKRUPT.

So, OVERSTOCK (ESG) is much more dangerous, is s significant business problem.

WHO IS WILLING TO BUY THOSE RAW MATERIAL?

When a quantity in a market thank to increase, what is suffering is the price.

(MACROECONOMICS PROBLEM)

A significant reduction in the average price means a significant reductions in margins (in company level). And when

margin is close to 0 there is no way to survive!!

Case 2: TAKES YEARS TO ADJUST.

The Bullwhip effect is the SUM of 2 components:

1. The former one is a significant amplification of how demand fluctuation by going from downstream to up-

stream along the supply chain or from the distribution stage to the component manufacturing stage.

2. And second, there is a gap, a misalignments between peaks and valleys along the supply chain.

In this way we might see a massive stockout or an ESG, so a massive overstock.

min 50 della reg.

USING ROP/EOQ

Go back to EOQ model.

Everything works as far as we are considering the finished products level.

Finished products:

- demand flat

- cumulative D is linear

- even linear, consumption of stock

Customer

The peak (impulse) of demand at the raw materials stage is not generated

by customers as the demand at the finished products stage is flat over

time.

I have 3 different EOQ:

1) Finished Product

2) Inv. Component

3) Inv. Raw Material

Quando in Finished Product arrivo a ROP —> ordino x componenti, i com-

ponenti sono flat —> quando arriva ROP nel FP la stock si svuota dalla

quantità ordinata, continua finché non arriva a ROP dei componenti e a

quel punto ordina “EOQ” di Raw material.

*impulse: imp(x) = 1/ 0 ; or 0 elsewhere This peak of dependent demand doesn’t cor-

respond to any peak in independent de-

mand. (guarda appunti cartacei).

The timing of this dependent demand is im-

possible to foresee.

The BULLWHIP means that even a flat de-

mand (independent) if bad managed can

create a huge peak of dependent demand

downstream.

INDEPENDENT DEMAND: deals with finished products.

DEPENDENT DEMAND: deals with components.

List Finished Product Components

BOMs + MPS + Inventory Level = Detailed Material Planning

Characteristics of PUSH (needs/requirements based) SYSTEMS.

OBJECTIVE:

Calculating which, how many and when components, sub‐assemblies, parts, raw materials etc.

are required to put a plan into operation.

i.e. to ensure that the customers’ orders due dates (deadlines) are respected

REQUIRED INFORMATION:

It is much greater than under pull systems, as it is needed to know the master production

schedule, the bills of materials and to consider at the same time all the data referred to

all the products and departments involved

REMARKS:

- Requirements of components directly depend on a plan

(e.g. the master production schedule)

- Requirements of components are therefore calculated and not estimated (i.e. deri-

ved from statistical analyses) as under pull systems

- In the end, the objective lies in coordinating the production dates (rendezvous) of

components to manufacture finished products

(or higher level components in the bill of materials)

MRP means Materials Requirements Planning and it represents the procedure that

implement the data processing needed by the push approach to manage inventories. :

MRP procedure operates – in a recurrent way – according to the so‐called 3S APPROACH

1. SUM the requirements of the same component coming from different orders and referred to the same period.

2. SPLIT the overall requirements per period of each component according to the lot-sizing policy.

3. SHIFT backward over time the lot‐sized requirements according to the lead times reported in the bills of materials

(to take into account the production routings).

This leads to a plan of purchasing and manufacturing ordering proposals.

- Explosion of the

This plan in turn generates gross requirements of lower‐level components BOM (Bill of Ma-

of the bill of materials.

- terials)

The recurrent procedure is finished when the raw materials (i.e. the “leaves” of the BoM)

are reached.

Before entering the first “S” (sum) you should know also the profile (over time) of the gross requirements (i.e. the de-

mand) of your item.

Gross requirements are divided into:

1. Internal requirements, i.e. originated from other finished products (e.g. a different kind of motorcycle)

2. External requirements, i.e. originated form customers (e.g. a chassis sold as spare part)

Now we enter the first “S” – sum: The gross total requirements of the chassis are give by the sum period by period of

the gross internal requirements and the gross external requirements.

Once the initial availability is finished, all the gross requirements are converted into requirements.

.

Now you have to take into account the 10%: scrap rate So, all the requirements are to be multiplied by 1.1

Now you have to take into account the orders in progress,

i.e. 48 pieces arriving at the beginning of period 3.

They represent some sort of additional availability, apart from that they are potentially subject to scraps , while availabi-

lity is not.

Inventory systems for dependent demand.

Now you have on hand the plan of orders for the chassis.

It has to be converted into gross requirements of the wheels and of the frame,

• i.e. of the lower‐level components (raw materials in the example)

These gross internal requirements of wheels coming from the chassis maybe have to be summed up with gross in-

• ternal requirements coming from other products and with gross external requirements (of the wheels) if they are sold

as spare parts

LIMITS OF THE MRP PROCEDURES

There are 3 major areas that referred to as “critical system design features” (Orlicky, 1974)

1. PRODUCTION CAPACITY IS INFINITE.

While all the production systems are capacity-constrained.

2. LEAD TIMES ARE FIXED AND PRE-DETERMINED.

While lead times result from the planning activity

3. DATA USED BY MRP.

And MRP is subject to the garbage-in-garbage-out (GIGO) law.

1. PRODUCTION CAPACITY IS INFINITE.

I. MRP basically operates at infinite capacity, so the

load of work centres is optimised only indirectly,

through lot‐sizing rules.

II. Production capacity is managed through

finite‐capacity post‐processors which are often

based on (complex) linear programming (LP)

and/or theory of constraints (ToC) approaches

2. LEAD TIMES ARE FIXED AND PRE-DETERMINED (a priori, outside MRP)

I. Lead times are used as input variables and they are not considered as function of (dependent on) the work load

- No protection is assured against the “orders in the past” phenomenon

- i.e. the orders that fall in periods prior to period 1, i.e. orders that would have had to be issued “in the past”

(yesterday, last week / month etc.)

II. Go back to the example of MRP running and suppose that the lead time of the chassis is 5 weeks instead of 3.

III. MRP uses lead times as input, while their actual value is an output

- Lead times are variable “by nature”, due to technology and organisation‐related factors

- No protection is assured against the “orders in the past” phenomenon i.e. the orders that fall in periods prior

to period 1. (i.e. orders that would have had to be issued “in the past” (yesterday, last week / month etc.)

IV. In the end, lead times estimation is critical:

- Underestimating lead times leads to stock‐out (of components) and therefore it puts the entire logic of the produc-

tion dates” in crisis.

- Overestimating lead times causes the planning horizon expansion, which implies:

A lower data reliability, since in the long term the portfolio will be composed of forecasts and fewer certain

• orders.

An increase of components stock holding costs as they are manufactured longer before the time they are

• actually needed.

V. In Lead times can be managed by shortening time buckets (E.g. by using days as bucke-

ts instead of weeks)

VI. : Shortening time buckets requires (more) accurate forecasts

and (more) frequent planning.

Example

A requirement scheduled for week 4 (if not “absorbed” by either availability or orders in progress) gives rise to

an order “in the past” at the raw materials stage under a weekly bucketing approach, while it gives rise to an order for

today under a daily bucketing approach.

3. DATA USED BY MRP REQUIRE A HUGE AMOUNT OF SPACE.

I. The volume of data is relevant, mainly for the bills of materials (BOMs)

- Consider“Taurus”tractor, equipped with different devices that correspond to various configurations of the

same “basic” product.

- To fully represent all the available alternatives for this (very simplified) example the (huge) number of bills of

materials required is: 3 x 2 x 5 x 2 x 2 x 3 x 3 = 1,080

II. To save space you can have to resort to super bills (product configurators)

- T hrough the analysis of commonalities, the bills of materials are arranged in modules (also called modular bills)

- Each module is a fictitious (artificial) bills that contains all the codes of one single option.

III. Strengths of super bills:

1. They reduce the required space by 1/100 ore even more:

- E.g. in the example of the Taurus tractor the number of bills of materials required is:

1 + 3 + 2 + 5 + 2 + 2 + 3 + 3 + n = 21 + n

- Which is anyway much less than:

3 x 2 x 5 x 2 x 2 x 3 x 3 = 1,080, i.e. the number of BoMs without super bills

hey remarkably help data maintenance and to keep data consistency

2. T

3. They dramatically improve accuracy of the forecasting process

- The sales forecasts over the medium‐long term, usually calculated only by product type (e.g. Taurus tractor) are con-

verted into (equally) reliable forecasts at the components / single option (part number) level.

- This allows a longer Master Production Schedule (MPS) horizon.

Executive summary

Materials Requirement Planning (MRP) systems make the ‘explosion’ of the bills of materials, by calculating (not esti-

• mating) which, how many and when components, sub‐assemblies, parts, raw materials etc. are required to ensure

that the customers’ orders due dates (deadlines) are respected:

- In the end MRPs coordinate the production dates (rendezvous) of components to manufacture finished pro-

ducts (or higher level components in the BoM)

• MRP is very useful to protect the inventory system against the bullwhip effect

• However, three major areas are referred to as critical system design features of MRP:

- MRP basically operates at infinite capacity

- Lead times are assumed as fixed and pre‐determined

- MRP requires a high volume of data

EXERCISE

DMPS SCHEDULING (13.11)

The production scheduling consists in the determination of:

- What, How Much, When and Where to produce.

1. At the level of single batch of each item and at machine level

2. On a short term horizon (normally weekly)

3. With temporal detail level, the day or the hour

DATA

- Production orders generated in the previous planning phases

- Resource availability

- Actual state of production system and inventory level

THE SITUATION

- Loading of the production plan defined in the MPS-MRP phas