**2.4 Scenario of three-stage production dispatch and manufacturing execution process**

The production scenario D minus 1 for the production process of one type of product with three stages of successive process, namely, welding, paint, and assembly are depicted in the production dispatching and manufacturing execution scheme shown in **Figure 6**.

On the first day (day 1; **Figure 6**), starting from the welding station, after making sure that the buffer material in front of the welding station (B1; **Figure 5**) is complete, the production dispatcher releases the B1 buffer for the welding process dispatch and the production executor at the welding station executes the welding process, while on this first day, the paint station and the second assembly is idle, waiting for the results of manufacturing execution at the welding station buffered on B2 (**Figure 5**) to be fed to the paint station the next day (the second day).

On the second day (day 2; **Figure 6**), the welding station repeats the welding process as done on the first day, while on the second day, the paint station has available buffer material for processing. After checking that the buffer material in front of the paint station is complete, the production dispatcher releases the buffer for the paint processing dispatch and the paint station production executor executes by carrying out the painting process, while on this second day, the assembly station is still idle, awaiting the results of manufacturing execution at

**17**

is 2 days.

*D Minus 1 Production Scenario: Production Model for Produced Hospital Furniture*

the painting station buffered on B3 (**Figure 5**) to be fed to the assembly station the

On the third day (day 3; **Figure 6**), the welding station and the paint station repeat the welding process as done on the second day, while on the third day, the assembly station has a ready component buffer available for assembly. After checking that the finished component buffer in front of the assembly station is complete, the production dispatcher releases the buffer for the dispatch assembly and the production executor at the assembly station carries out the manufacturing execution by carrying out the assembly process to produce finished goods buffered at B0. On the third day, all three workstations carry out manufacturing executions simultaneously, and this process is repeated in the following days until the specified

The production model scenario D minus 1 use the planning time horizon based on shipping time (ST). This time is described in relation from the beginning of the production process to the completion process (finished goods are sent or stored in warehouses), for all stages of the production process shown previously in **Figure 2**. The work reference is on day 0 (D0), which is the day when the assembly process starts (start assembly), for that on day D-1 (start painting) the painting process must be sure to run, and on day D-2 (start welding) welding process must also be sure to run.

The processing time in the case of three process steps for the welding, paint, and assembly processes is the same as the ST-2 days. While the waiting time to be able to start the painting process is 1 day, while the waiting time for the assembly process

**2.5 Planning horizon of the production model D minus 1**

*DOI: http://dx.doi.org/10.5772/intechopen.93691*

next day (the third day).

*Production dispatch and manufacturing execution scenarios.*

**Figure 6.**

shipping time is found.

*D Minus 1 Production Scenario: Production Model for Produced Hospital Furniture DOI: http://dx.doi.org/10.5772/intechopen.93691*

#### **Figure 6.**

*Concepts, Applications and Emerging Opportunities in Industrial Engineering*

other station waits because there is no buffer. This is a situation where the buffer is not sufficient to supply an assembly station that is designed to operate at a certain

must be available from B11 to B1n to be fed to the welding station. Meanwhile, to be fed to the paint part, there must be enough buffers B21 to B2n available. Furthermore, to be fed to the assembly station, B31 to B3n buffers must also be available in sufficient

work out provided from the WIP buffer of finished goods B01 to B0n.

To overcome this, a buffer scenario is created on day D--2, where sufficient buffers

The buffer that needs to be provided is work in. This buffer must be ensured on day D-3 already available, while through the WIP controller the input entered into the system must be controlled, the input is work released, while the throughput is

Through this model, it can be stated that the controlled parameter is WIP in the system, while the manipulated parameter is the upstream buffer in each machine system of the three processing machines. By using the principles of control, of course by controlling WIP through the manipulation of parameters of the production

**2.4 Scenario of three-stage production dispatch and manufacturing execution** 

The production scenario D minus 1 for the production process of one type of product with three stages of successive process, namely, welding, paint, and assembly are depicted in the production dispatching and manufacturing execution

On the first day (day 1; **Figure 6**), starting from the welding station, after making sure that the buffer material in front of the welding station (B1; **Figure 5**) is complete, the production dispatcher releases the B1 buffer for the welding process dispatch and the production executor at the welding station executes the welding process, while on this first day, the paint station and the second assembly is idle, waiting for the results of manufacturing execution at the welding station buffered on B2 (**Figure 5**) to be fed to the paint station the next day (the second day).

On the second day (day 2; **Figure 6**), the welding station repeats the welding process as done on the first day, while on the second day, the paint station has available buffer material for processing. After checking that the buffer material in front of the paint station is complete, the production dispatcher releases the buffer for the paint processing dispatch and the paint station production executor executes by carrying out the painting process, while on this second day, the assembly station is still idle, awaiting the results of manufacturing execution at

**16**

capacity.

**Figure 5.**

quantities.

**process**

process, it is expected to succeed.

*Timing process in production model scenario D minus 1.*

scheme shown in **Figure 6**.

*Production dispatch and manufacturing execution scenarios.*

the painting station buffered on B3 (**Figure 5**) to be fed to the assembly station the next day (the third day).

On the third day (day 3; **Figure 6**), the welding station and the paint station repeat the welding process as done on the second day, while on the third day, the assembly station has a ready component buffer available for assembly. After checking that the finished component buffer in front of the assembly station is complete, the production dispatcher releases the buffer for the dispatch assembly and the production executor at the assembly station carries out the manufacturing execution by carrying out the assembly process to produce finished goods buffered at B0. On the third day, all three workstations carry out manufacturing executions simultaneously, and this process is repeated in the following days until the specified shipping time is found.

#### **2.5 Planning horizon of the production model D minus 1**

The production model scenario D minus 1 use the planning time horizon based on shipping time (ST). This time is described in relation from the beginning of the production process to the completion process (finished goods are sent or stored in warehouses), for all stages of the production process shown previously in **Figure 2**. The work reference is on day 0 (D0), which is the day when the assembly process starts (start assembly), for that on day D-1 (start painting) the painting process must be sure to run, and on day D-2 (start welding) welding process must also be sure to run.

The processing time in the case of three process steps for the welding, paint, and assembly processes is the same as the ST-2 days. While the waiting time to be able to start the painting process is 1 day, while the waiting time for the assembly process is 2 days.

The complete planning horizon for D minus 1 production scenario is illustrated in **Figure 7**. In this figure, the total amount produced during the ST period is expressed in Dt (units), the amount produced daily is Dp (units), and the daily processing time for one shift is Tp = 8 h.

The D minus 1 scenario will be able to be effectively applied to a hospital furniture factory with a daily production plan of more than one type of product (n types of products), because the obstacle is that, at a painting station, one painting station will get feed n buffer components from B21 to B2n and must produce finished components which are buffered into n buffers in B31 through B3n which will be fed to n assembly stations.

The painting process model is multi-buffer input, single machine, and multibuffer output, where the buffer output cannot be received immediately even though the input buffer has been fed to the paint station, and the product can only be received at the buffer output after the paint station completes one rotation cycle, and the waiting time for waiting for the first output out of the painting plant is about 90 min.

The results of this paint will later be placed in buffers B31 through B3n to be fed to n assembly stations, so if the bait scenario uses the *hot from the oven* method, the waiting time constraints on each assembly station will be a waste, and to overcome this, use the production model D minus 1 with prepared component buffer on minus 1 day before the component is assembled into finished goods. Examples of scenarios for managing four types of products are shown in **Figure 8**.

#### **2.6 Production schedule and example of D minus 1 operation**

Production schedule is setup used mathematical Heaviside step function *H*(*t*) [18]:

$$H(t) = \begin{cases} \mathbf{0} \xrightarrow{for} t \le \mathbf{0} \\ \mathbf{1}\_{for} \\ \mathbf{1} \xrightarrow{for} t > \mathbf{0} \end{cases} \tag{1}$$

Using *Ddi* as the stimulus and ST is total planning horizon. General time respond *Dp* at time *t* for every number of period *k* of time period *Td* which is time period of a process to finish *Ddi* product in a day can be determine as:

$$Dp(t,k) = D\_{dl} \left( H(t - kT\_d) - H(t - kT\_d - T\_d) \right) \tag{2}$$

*k* = 1, 2, 3, ST

With Eq. (2) can be determined day-to-day production schedule in each workstations as seen in Eqs. (3)–(5); each is respectively scheduled for welding, painting, and assembly.

$$Dpk(t,k) = D\_{di}\left(H\left(t - (k-1)T\_d\right) - H\left(t - (k-1)T\_d - T\_d\right)\right) \tag{3}$$

$$Dpc(t,k) = D\_{di} \left( H(t - kT\_d) - H(t - kT\_d - Td) \right) \tag{4}$$

**19**

and so on.

**Figure 8.**

**Figure 7.**

days) production activity is off.

as shown in **Figure 9**.

*D Minus 1 Production Scenario: Production Model for Produced Hospital Furniture*

*Scheme of the complete planning horizon of D minus 1 production planning scenario.*

For planning production activity used Eq. (3), Eqs. (4) and (5). Base on those equation be developed application module using Matlab software for setup production schedule. Sample of production schedule is shown in **Table 1**. This is the table of production activity for delivering order of 96 unit products of hospital bed, Supramak 73,006, with daily production of 32 units, with shipping time 5 days; production period is 2÷7 February 2017, in this period at date of 5 February (holi-

*The planning horizon scenario for the production model D is minus 1 to produce four types of products.*

The following will show the scenario D minus 1 of production schedule of **Table 1** to produce products with a total volume of Dt = 96 units, lead time ST = 5 days, daily production plan Dd = Dt/(ST-2) = 96/3 = 32. From this production plan, the production process scenario for the welding cycle time tweld = 18 min

This is a daily production scheme for welding stations using a daily process period of one shift is Tp = 8 h, 1 day is 24 h, so the 24th hour represents the first day, the 48th hour indicates the second day, the 72th hour denotes the third day

*DOI: http://dx.doi.org/10.5772/intechopen.93691*

$$Dpa(t,k) = D\_{di}\left(H\left(t - (k+1)T\_d\right) - H\left(t - (k+1)T\_d - T\_d\right)\right) \tag{5}$$

*D Minus 1 Production Scenario: Production Model for Produced Hospital Furniture DOI: http://dx.doi.org/10.5772/intechopen.93691*

#### **Figure 7.**

*Concepts, Applications and Emerging Opportunities in Industrial Engineering*

processing time for one shift is Tp = 8 h.

assembly stations.

about 90 min.

*k* = 1, 2, 3, ST

and assembly.

The complete planning horizon for D minus 1 production scenario is illustrated

The D minus 1 scenario will be able to be effectively applied to a hospital furniture factory with a daily production plan of more than one type of product (n types of products), because the obstacle is that, at a painting station, one painting station will get feed n buffer components from B21 to B2n and must produce finished components which are buffered into n buffers in B31 through B3n which will be fed to n

The painting process model is multi-buffer input, single machine, and multibuffer output, where the buffer output cannot be received immediately even though the input buffer has been fed to the paint station, and the product can only be received at the buffer output after the paint station completes one rotation cycle, and the waiting time for waiting for the first output out of the painting plant is

The results of this paint will later be placed in buffers B31 through B3n to be fed to n assembly stations, so if the bait scenario uses the *hot from the oven* method, the waiting time constraints on each assembly station will be a waste, and to overcome this, use the production model D minus 1 with prepared component buffer on minus 1 day before the component is assembled into finished goods. Examples of

Production schedule is setup used mathematical Heaviside step function *H*(*t*) [18]:

0 0

(1)

*for*

*for t*

Using *Ddi* as the stimulus and ST is total planning horizon. General time respond *Dp* at time *t* for every number of period *k* of time period *Td* which is time period of

With Eq. (2) can be determined day-to-day production schedule in each workstations as seen in Eqs. (3)–(5); each is respectively scheduled for welding, painting,

1 0

*t*

*Dp t k D H t kT H t kT T* ( , ) = − − −− *di*( ( *<sup>d</sup>* ) ( *d d* )) (2)

*Dpk t k D H t k T H t k T T* ( , ) = −− − −− − *di*( ( ( 1) *<sup>d</sup>* ) ( ( 1) *d d* )) (3)

*Dpa t k D H t k T H t k T T* ( , ) = −+ − −+ − *di*( ( ( 1) *<sup>d</sup>* ) ( ( 1) *d d* )) (5)

*Dpc t k D H t kT H t kT Td* ( , ) = − − −− *di*( ( *<sup>d</sup>* ) ( *<sup>d</sup>* )) (4)

 → ≤ <sup>=</sup> → >

scenarios for managing four types of products are shown in **Figure 8**.

( )

*H t*

**2.6 Production schedule and example of D minus 1 operation**

a process to finish *Ddi* product in a day can be determine as:

in **Figure 7**. In this figure, the total amount produced during the ST period is expressed in Dt (units), the amount produced daily is Dp (units), and the daily

**18**

*Scheme of the complete planning horizon of D minus 1 production planning scenario.*

#### **Figure 8.**

*The planning horizon scenario for the production model D is minus 1 to produce four types of products.*

For planning production activity used Eq. (3), Eqs. (4) and (5). Base on those equation be developed application module using Matlab software for setup production schedule. Sample of production schedule is shown in **Table 1**. This is the table of production activity for delivering order of 96 unit products of hospital bed, Supramak 73,006, with daily production of 32 units, with shipping time 5 days; production period is 2÷7 February 2017, in this period at date of 5 February (holidays) production activity is off.

The following will show the scenario D minus 1 of production schedule of **Table 1** to produce products with a total volume of Dt = 96 units, lead time ST = 5 days, daily production plan Dd = Dt/(ST-2) = 96/3 = 32. From this production plan, the production process scenario for the welding cycle time tweld = 18 min as shown in **Figure 9**.

This is a daily production scheme for welding stations using a daily process period of one shift is Tp = 8 h, 1 day is 24 h, so the 24th hour represents the first day, the 48th hour indicates the second day, the 72th hour denotes the third day and so on.


**Table 1.**

*73,006 Supramak bed production schedule.*

**Figure 9.** *Example scenario at a welding station. Total production of 96 units, ST = 5 days.*

From **Figure 9** at eighth hour, the welding process to finish 32 products should have been completed, but the process was still running (overshoot capacity Td > Tp) to completing the process through extra time (overtime). The occurrence of overtime is due to the available daily production capacity is lower than demand, the indicator is weld cycle time > takt time (18 > 15 min), in this case the overtime that needs to be provided is (18–15) 32 = 96 min.

To avoid overtime in the welding process, in planning the production process, it must be ensured that takt time ≥ cycle time, because takt time indicates the production capacity is associated with workload (number of requests).

The semifinished component buffer for the painting station provided by the welding station the day before was in complete condition, then the component was painted with the process scenario as shown in **Figure 10**.

The complete component supply before leaving the painting station as a finished component, is first circulated throughout the paint station track using a conveyor, so there is a delay in processing time to start the painting process waiting for the finished component to be the first to leave the paint station. In **Figure 10** shown at 24 h.

This delay will reduce the time available for the Tp process to Tp-waiting time, and act as potential to cause a delay in the process of completing the workload (overtime) and this will occur if the number of complete components forming the finished product requires the same cycle time or greater than takt time. But if the paint cycle time is far less than the takt time, then before the process runs out the workload has been completed so that there is still available remaining time and capacity (**Figure 10**), this remaining time can be used to process other types of products.

**21**

available processing time.

**Figure 10.**

**Figure 11.**

**2.7 Production dashboard**

*D Minus 1 Production Scenario: Production Model for Produced Hospital Furniture*

The finished component buffer for the assembly station provided by the welding station 1 day before is available in complete condition, then the component is assem-

At the assembly station, the process of assembling finished goods can be directly carried out without any waiting time, if the time of the assembly cycle (ta) of the finished product is close to the takt time price then the possibility of overtime can be reduced. **Figure 11** shows that Tp processing time can be utilized maximally, and in this case, overtime does not occur or the process is finished faster than the

Operational model of D minus 1 production scenario can be managed using a production dashboard [19]. Starting with production schedules, buffering at each production station and production simulation to total product demand can be demonstrated using this dashboard. Also, daily production activity and calculating the time delay when production cannot be met the target can be demonstrated too. This dashboard besides to simulate production activities based on cycle time and takt time also provides applications to show the response of the production system as a dynamic system.

bled with the assembly process scenario as shown in **Figure 11**.

*Example scenario at an assembly station. Total production of 96 units, ST = 5 days.*

*Example scenario at the paint station. Total production of 96 units, ST = 5 days.*

*2.7.1 Production planning and scheduling (PPS) dashboard*

*DOI: http://dx.doi.org/10.5772/intechopen.93691*

*D Minus 1 Production Scenario: Production Model for Produced Hospital Furniture DOI: http://dx.doi.org/10.5772/intechopen.93691*

#### **Figure 10.**

*Concepts, Applications and Emerging Opportunities in Industrial Engineering*

**Process 01-Feb 02-Feb 03-Feb 04-Feb 05-Feb 06-Feb 07-Feb** Supply 32 32 32 0 0 0 0 Welding 0 32 32 32 0 0 0 Painting 0 0 32 32 0 32 0 Assembly 0 0 0 32 0 32 32

From **Figure 9** at eighth hour, the welding process to finish 32 products should have been completed, but the process was still running (overshoot capacity Td > Tp)

overtime is due to the available daily production capacity is lower than demand, the indicator is weld cycle time > takt time (18 > 15 min), in this case the overtime that

To avoid overtime in the welding process, in planning the production process, it must be ensured that takt time ≥ cycle time, because takt time indicates the production capacity is associated with workload (number of requests).

The semifinished component buffer for the painting station provided by the welding station the day before was in complete condition, then the component was

This delay will reduce the time available for the Tp process to Tp-waiting time, and act as potential to cause a delay in the process of completing the workload (overtime) and this will occur if the number of complete components forming the finished product requires the same cycle time or greater than takt time. But if the paint cycle time is far less than the takt time, then before the process runs out the workload has been completed so that there is still available remaining time and capacity (**Figure 10**), this remaining time can be used to

The complete component supply before leaving the painting station as a finished component, is first circulated throughout the paint station track using a conveyor, so there is a delay in processing time to start the painting process waiting for the finished component to be the first to leave the paint station. In **Figure 10** shown

to completing the process through extra time (overtime). The occurrence of

needs to be provided is (18–15) 32 = 96 min.

process other types of products.

painted with the process scenario as shown in **Figure 10**.

*Example scenario at a welding station. Total production of 96 units, ST = 5 days.*

**20**

at 24 h.

**Figure 9.**

**Table 1.**

*73,006 Supramak bed production schedule.*

#### **Figure 11.**

*Example scenario at an assembly station. Total production of 96 units, ST = 5 days.*

The finished component buffer for the assembly station provided by the welding station 1 day before is available in complete condition, then the component is assembled with the assembly process scenario as shown in **Figure 11**.

At the assembly station, the process of assembling finished goods can be directly carried out without any waiting time, if the time of the assembly cycle (ta) of the finished product is close to the takt time price then the possibility of overtime can be reduced. **Figure 11** shows that Tp processing time can be utilized maximally, and in this case, overtime does not occur or the process is finished faster than the available processing time.

#### **2.7 Production dashboard**

#### *2.7.1 Production planning and scheduling (PPS) dashboard*

Operational model of D minus 1 production scenario can be managed using a production dashboard [19]. Starting with production schedules, buffering at each production station and production simulation to total product demand can be demonstrated using this dashboard. Also, daily production activity and calculating the time delay when production cannot be met the target can be demonstrated too. This dashboard besides to simulate production activities based on cycle time and takt time also provides applications to show the response of the production system as a dynamic system.

This dashboard to display production simulation with scenario D minus 1 is called the production planning and scheduling (PPS) dashboard. The PPS dashboard display is shown in **Figure 12**.

Production planning and scheduling can be setup on the dashboard. Before production, event schedule executed the schedule simulated using relevant parameter of production control. If by simulation target of production can be achieved, the scheduled plan decided to be used as production schedule in production floor. But if schedule failure, must be set up new production parameter to control and optimization the process, and with the new parameter once again the production event must be simulated. If the process objective can be fulfilled by this parameter, then the parameter is used in the production schedule.

Control parameter provides in the prototype PPS dashboard, and the parameters used to simulate production process are takt time and cycle time. Cycle time, which is higher than takt time, means capacity of production is lower than the customer demand. For this case the production system is multistage production it is mean all cycle time in each production stage must be equal or lower than takt time. If one of cycle time higher than the takt time, production output will not full fill the customer demand, also there is a bottleneck in one of production stage certainly. If the difference of the takt time and cycle time relatively small, the solution is using extra time in the production floor. But if the difference significantly high the production system must add production time shift.

Control parameter can be directly input to the dashboard use block *Input Parameter* as shown in **Figure 12**. Also using facility provide in the windows dashboard system is with push menu *Input Production Parameter* which is prompt input dialog for input control parameter, the result also displayed in block Input Parameter. For simulate the process must be push each process menu, *Welding* 

#### **Figure 12.**

*Production planning and scheduling (PPS) dashboard. The dashboard consists of: 1.Dashboard name, 2. Simulation Title, 3. Dashboard Menu, 4. Input parameters, 5. Product name and production schedule, 6. Simulation Results, 7. Graph Display, and 8. Dynamic system display.*

**23**

**Figure 13.**

*D Minus 1 Production Scenario: Production Model for Produced Hospital Furniture*

*Buffer*, *Paint Shop Buffer* or *Assembly Buffer*. To show all process must be push menu

The simulation sample shown in **Figure 12** is simulation of production to produce total customer demand 120 units hospital bed, for shipping time 5 days and day demand is 40 units. Takt time 12 min, cycle time in welding station is 13 min, in paint shop is 7.25 min and in assembly 12 min. Simulation result is shown in

The dashboard also provide compare between target and realization for any day of production, if there is any difference between target and realization the dashboard will show bottleneck time also need of extra time to finishing the task. If the differences can be accepted use menu in Input parameter to save the production

*2.7.2 Production execution management and production information management* 

To control production process provide production execution management (PEM) dashboard and production information managements (PIM) dashboard, both dashboard bundle in a single dashboard call as PEMPIM dashboard [19]. The architecture of the dashboard is shown in **Figure 13**, and the windows

1.File menu: For operating file among other open file, save file and close

2.Bill of Materials (BOM) information and status of components supply menu: It is for manufacturing control purposes, consist information of supply com-

3.Outstanding orders menu: It is for execution purpose of production. This consists of menu for give information of the order status, status finish good in

*DOI: http://dx.doi.org/10.5772/intechopen.93691*

*Display result*.

planning.

*Simulation Result* block.

*dashboard*

windows.

dashboard is equipped with menu:

ponents to ensure that supply is complete.

ware house and product delivery to customers.

*Production execution management and production information management dashboard.*

*D Minus 1 Production Scenario: Production Model for Produced Hospital Furniture DOI: http://dx.doi.org/10.5772/intechopen.93691*

*Buffer*, *Paint Shop Buffer* or *Assembly Buffer*. To show all process must be push menu *Display result*.

The simulation sample shown in **Figure 12** is simulation of production to produce total customer demand 120 units hospital bed, for shipping time 5 days and day demand is 40 units. Takt time 12 min, cycle time in welding station is 13 min, in paint shop is 7.25 min and in assembly 12 min. Simulation result is shown in *Simulation Result* block.

The dashboard also provide compare between target and realization for any day of production, if there is any difference between target and realization the dashboard will show bottleneck time also need of extra time to finishing the task. If the differences can be accepted use menu in Input parameter to save the production planning.
