Klausur

Product which contains of different parts and end product is something like a car or airplane

Product which is manufactured without being interrupted. Mostly some high volume products without the need for customization

-       Complex production processes

-       No complex product structure (The parts of which an end product consists are easily to understand)

-       Often different end products from one source product (e.g. 2. 000 steel grades (Stahlsorten), can be produced from one source product (hot metal))

-       Inflexible product mix. Production with dependent setup costs, limitations of systems and waiting times

-       Inflexible facilities in regards to production volume, they always try to reach a 24 hours utilization per day.

combining different processes or services to produce a product which satisfies the customer

A chain of activities which directly delivers value to customers

Provides resources and inputs for the core process

-       New service/ product development process

-   Design and develop new services or products from inputs received from external customer specification

-       Supplier relationship process

-   Select suppliers of services, materials and information and facilitate the flow of these items into the firm

-       Order fulfillment process

-   The activities required to produce and deliver the service or product to the customer

-       Customer Relationship process

-   Identify, attract and build relationships with customers and facilitate the placement of orders

All of these processes can be connected with each other

-       Data can easily transferred between physical things and software (IOT)

-       Monitoring is easy with RFID technology

-       Methods for analyzing the extensive data like big data

-       Decision support tools are increasing (AI and Operations Research)

-       Automation with robots and scheduling

-       Predictive maintenance based on computer calculations

-       People are still important, for example for being a role model for behavior

-       Find the “optimal” reaction to short term events  Most of the scheduling problems are NP-Problem(Easy to detect the problem, but hard to solve)

-       Trade-off between productivity and flexibility. Always a tradeoff between these two dimensions must be considered

-       Forecast the development of the economy

-       Flow of different tasks which is executed by limited resources +++ waiting (queueing) results in waiting times

-       The order which tasks is executed can be determined in advance or in short-term

-       It can either be forecast driven or customer order driven processes

-       Either Customer specific and standard products/ services

Operations management is about running all parts of a business, like services, transportation, and retail, in addition to manufacturing. Manufacturing management focuses specifically on making things, including designing products and processes, and controlling production.

The flow between the Input and Output

-       Expressed as quantities: Productivity

-       Expressed as value: Money

-       Mixed: Value added productivity

-   SCOR (Supply chain operations reference): Model to measure the effectiveness of the supply chain.

Limitation: Efficient production of a specific quantity relies on fixed relationships among input factors; the quantity of the bottleneck resource strictly determines the upper limit of production.

Linearity: Linear relations between the input quantities of the resources and the output quantities. —> Linear-limitational production functions are commonly termed Leontief

Component capacity amount is fixed per unit, every end product needs the same amount of input goods

Linear cost fucntions, variable costs per unit of product

-       Make to Stock (MTS): Produce based on forecasted customer demand

-       Assemble to Order (ATO): Components are already finished but are just getting assembled after the order of the customer

-       Make to Order (MTO): Produce only after customer has placed the order

-       Engineer to Order (ETO): Product is getting engineered produced after the order

-       Flow Time (cycle time): Time a product needs to be produced (incl. waiting time)

-       Delivery time: Time the order needs to arrive at the customer

-       Inventory Level: Level of the inventory for SKU (stock keeping units) such as raw materials, finished components and WIP (Work in Process)

-       Due date performance: Percentage of orders that are late

-       SCOR Model Overview: Developed by the Supply-Chain Council as a standard diagnostic tool for supply-chain management across industries.

-       Purpose: Aids in addressing, improving, and communicating supply-chain management practices among all relevant parties.

-       Functionality: Describes business activities throughout all phases of fulfilling customer demand using standardized process building blocks.

evidence in the literature indicates manufacturers, on average, do not report experiencing tradeoffs among the competitive dimensions of quality, delivery, flexibility, and cost as suggested by the classical tradeoffs model.

Positive: Inventories are costly, but they

·       Allow production smoothing over time,

·       Make savings in setups possible (due to higher lot sizes)

·       Act as a buffer against uncertain (scarp, unreliable suppliers, etc.)

Negative: Inventories degrade performance because they

·       Increase dependence on demand forecasts – safety stocks, etc.

·       Hide inefficiencies,

·       Eliminate the pressure to improve the processes!

ð  Unbalanced capacities, unreliable manufacturing processes and suppliers, high setup times, etc. remain unchanged.

As more inventory is on stock, the more problems are hided by them because the overload of inventories is hiding some inefficienes

A production concept is a theory-based guiding principle for the design, control and development of production systems that is often based on experience and aims at improving competitiveness of the company in the long and short term. It consists of a description of the optimal state of the technical and economic elements of a production system and their relationships to each other, practical (application oriented) design recommendations as well as methods and instruments that are necessary to achieve the desired state.

(1) Cycle Time = value-added time + non-value-added time

(1’) -> Tautology of (1): Every hour a production order spends in the manufacturing system is either                             value-added time or non-value-added time.

(2) Decreased non-value-added time -> increased efficiency

(3)  Everyone in the world is either Hillary R. Clinton or is not Hillary R. Clinton

1.     Observation.

2.     Classification.

3.     Theoretical Conjecture.

4.     Experimental verification/refutation.

5.     Repeat.

• Guiding principle: “Eliminate waste" - consistent focus on productivity or economic efficiency, resp.

• Countermeasures against presumed weaknesses in organizations.

• Short-term trade-offs are not accepted! Assumption: These trade-offs can be overcome by continuous improvement (organizational learning, kaizen).

• Long-term trade-offs: How far are improvements economically reasonable? Capacity flexibility, optimal quality level, shortening of set-up times, etc. => thinking in trade-offs vs. thinking in organizational learning processes! "Strategy of management of complex systems" (F. Malik)

• Analysis and improvement of processes - sound theoretical basis is important

·       Science can tell us which states of the world can be achieved and which cannot.

·       This is the same in our discipline although the boundary seems to be “fuzzy”.

·       We need laws of material flows that provide “basic relationship among fundamental manufacturing quantities” Note: Causal relationships between changes in manufacturing and improving KPIs can be identified! Implications: We can identify the impact of new technologies (e.g. IT) on KPIs.

·       These basic relationship are influenced by human behaviour – people execute the processes and make decisions on lot details. Implication: Limitations on the predictability.

·       In the following we derive the “basic relationships among fundamental manufacturing quantities”  by axiomatic research.

·       Variability Law:            Increasing variability always degrades the performance of a production                                    system.

·       Law (Conservation of Material):          In a stable system, over the long run, the rate out of                                                    a system will equal the rate in, less any yield loss,                                                        plus any parts production within the system.

·       Capacity Law:  In steady state, all plants will release work at an average rate that is strictly                  less than average capacity. (Never reach 100%)

·       Utilization Law:            If a station increases utilization without making any other change, average                   WIP and cycle time will increase in a highly nonlinear fashion.

·       Buffering Law: Systems with variability must be buffered by some combination of: 1. Inventory 2. Capacity 3. Time

·       Buffer Flexibility Corollary:      Flexibility reduces the amount of variability buffering                                                   required in a production system. Examples: Generic stock (assemble-to-order), cross-trained workers, flexible lead time quotation Formal model: one M/M/s instead of s M/M/1 models (see Average flow time for M/M/s systems with different number s of parallel servers)