Study contribution

Each type of the five systems has its contribution. Figure 3.2 shows the contributions where some of them are the same. The size of contribution in electronic kanban is larger than that for traditional kanban because the first one did not get the attention from the researchers. There are some items that are in the two kanban systems because of the similarities in the two systems. For example, analytical investigation was done at first for electronic kanban. Then the formulas were altered to fit traditional kanban as will be seen in chapter 4.

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Decentralized supermarket Main warehouse

a. Demand-oriented system

Traditional Kanban Electronic kanban

b. Kanban system

c. Dynamic planning Figure 3.2 Study contribution

Fixed routing:

1. Considering fixed routing problem 2. Considering minimizing the

number of trailers

3. Accommodate capacity problems using a systematic way of four strategies

a. Supermarket location problem: 1. Considering the availability of

areas beside workstations for possible supermarkets 2. Considering the capacity of

supermarkets

b. Routing, scheduling, and loading problems:

1. Studying the three problems together

2. Considering minimizing system variability

3. Further decreasing the total inventory holding costs

a. Analytically studying the system to find the relationship between starvation and number of kanban/ circulating inventory size

b. Finding ALSI.

c. Investigating if market attendant or automatic loading should be used

a. Introducing a new concept, namely, AEK, to face capacity problems

b. Introducing a cost model c. Routing problem: simplified

way based on average demand.

A mix between demand-oriented and e-kanban

1. Dynamic material flow planning approach that considers peak demand periods 2. Accommodating disturbances such as defective parts, line stoppage, machine

breakdown, and resequencing

40 3.3 Tools used in the study

The study depends mainly on operations research, analytical investigation, and simulation. Figure 3.3 shows the assignment of the tools used for each system. Some numerical examples similar to that found in the literature were used. As in figure 3.3, there are some similarities between some systems due to the similarity of general conditions. Compared to that in traditional kanban, the analytical investigation done in electronic kanban have some similarities but also some new dimensions.

Decentralized supermarket Main warehouse

a. Demand-oriented system

Traditional kanban Electronic kanban

b. Kanban system

c.

d. Dynamic planning

Figure 3.3 Tools used in the study

Fixed routing:

1. Integer programming 2. Dynamic programming 3. Analytical investigation. a. Supermarket location problem:

1. Genetic algorithm b. Routing, scheduling, and

loading problems: 1. Analytical investigation 2. Integer programming 3. Dynamic programming a. Analytical investigation b. Simulation

A mix between demand-oriented and e-kanban a. Analytical investigation

41 Table 3.1 study inputs and outputs

Inputs Outputs

1. Type of material control system used:

– Demand-oriented (centralized and decentralized) – Traditional kanban

– Electronic kanban – Dynamic planning

2. Type of inventory system: – Centralized warehouse – Decentralized supermarket

• Available areas for supermarkets and (x, y) locations

3. Stations:

– Demand (averaged and detailed if possible) – Exact location (x, y)

– Loading and unloading needed times – Path of flow for product models

– Maximum line-side capacity for inventory – Idea safety stock size

4. Costs:

– Unit inventory holding costs – Product model price

– Tugger train investment cost – Material operator cost

– Material handling cost per unit distance per bin – Installation cost of decentralized supermarket 5. Trains

– Capacity (number of bins, number of trailers, number of bins per trailer)

– Speed (average)

– Loading and unloading time at supermarket – Number available

6. Decisions that may be enforced by management – Cycle time

– Maximum allowed starvation percentage.

1. Supermarket best locations and number (if any)

2. Routing (trains assignment to stations)

3. Needed number of trains and trailers per train

4. Cycle time and the starting time of each route (scheduling).

5. Loading (bins types and quantities to be loaded in each route).

6. Optimal number of kanban (if any) 7. Optimal circulating inventory size (in

the case of e-kanban)

8. Workstation starvation (in the case of using kanban)

9. ALSI for each station 10. Total system costs 11. Number of extra trailers

42 3.4 Study inputs and outputs

To utilize all the capabilities of the study, the needed input of information and the output results are in table 3.1. To design the milk run system and define its parameters, a lot of information is needed. Some information is raw data such as locations of workstations. However, some information is the results of decisions of management such as maximum allowed workstation starvation percentage. In the case of fixed routing, the average expected workstation demand for the long range is required. So forecasting must be done. Some information needs some judgment by the decision maker such as the fixed cost of using decentralized supermarkets.

3.5 Summary

This chapter defines the general scope of the study where five different milk run systems were considered. It also defines the types of cost the study tries to minimize, the contribution in the different systems, tools used, and inputs and outputs of the study. The situation on the ground defines which system to use. E-kanban for example needs technical support in the form of bar code or RFID. The accuracy of expecting the demand for parts by each station is the motive to use demand-oriented system. If there are some disturbances that need fast reaction, then a hybrid system which combines the advantages of e-kanban and demand-oriented systems is needed. There are some similarities and differences in the planning tasks between the five systems. This chapter is important to understand the general concept of the thesis.

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