Enabling industrial internet of things-based digital servitization in smart production logistics

Figures & data

Figure 1. Proposed architecture for Industrial Internet of Things-enabled digital servitization in smart production logistics.

Figure 2. Proposed data model for multichannel communication in Industrial Internet of Things-enabled digital servitization for smart production logistics.

A data model for multichannel communication including IIoT modelling profiles, data bases, production logistics tasks, and services.

Figure 3. Proposed industrial internet of things digital servitization for smart production logistics function profile.

Function profile for IIoT-enabled digital servitization describing the functions, parameters, connectors and stereotypes for smart production logistics.

Figure 4. Proposed industrial internet of things digital servitization for smart production logistics database profile.

Database profile for IIoT-enabled digital servitization describing the parameters for material handling tasks in smart production logistics.

Figure 5. Monitoring, optimisation, control, and autonomy services in material handling for the Industrial Internet of Things-enabled digital servitization for smart production logistics.

Example of IIoT-enabled digital servitization for smart production logistics in material handling including monitoring of status, optimisation of schedule, control of routes, and autonomy in the execution of tasks.

Figure 6. Proof-of-concept prototype in a laboratory environment.

Layout of laboratory environment including 10 stations, six Radio Frequency Identification Device sense point, an Ultra Wide Band Width tag, and one automated guided vehicle.

Figure 7. Screenshot of the monitoring service for material handling for the proof of concept.

Spaghetti diagram and status of an automated guided vehicle during execution of material handling tasks in a proof of concept laboratory environment.

Figure 8. Screenshot of the control service in the proof of concept.

Route optimisation for automated guided vehicle during the execution of material handling tasks in a proof of concept laboratory environment.

Figure 9. Screenshot of the autonomy services in the proof of concept utilising MiR software.

Automatic execution of tasks in material handling including the use of an automated guided vehicle in a proof of concept laboratory environment.

Figure 10. Results from the data-drive optimal schedule of material handling tasks in smart production logistics.

Results of optimised schedule of tasks in material handling comparing makespan and takt time.

Table A1. Notations for optimisation model.

$\mathbf{T}$	task set
$\mathbf{F}$	AGVs set
${\mathbf{T}}_i$	task i
${\mathbf{F}}_j$	AGV j
${\mathbf{C}\mathbf{P}}_i$ and ${\mathbf{C}\mathbf{P}}_j$	current position of task i and AGV j
${\mathbf{N}\mathbf{D}}_i$ and ${\mathbf{N}\mathbf{D}}_j$	destination of task i and AGV j
${\mathbf{W}}_i$	weight of task i
${\mathbf{V}}_i$	volume of task i
${\mathbf{S}\mathbf{V}}_j$	surplus weight of vehicle j
${\mathbf{S}\mathbf{W}}_j$	surplus volume of vehicle j
${\mathbf{w}}_i$	weight of objective variables
$T{s}_i$	starting delivery time of task i
$TF{s}_{ij}$	the starting time of AGV j with task i
$TF{c}_{ij}$	the completing time of AGV j delivering task i
$T{c}_j$	the completing time of AGV j
$T{d}_i$	the needed delivery time of task i
D	total distance of AGV
$D_{\mathrm{f}\mathrm{u}\mathrm{l}\mathrm{l}}$	distance of AGV with tasks
$D_{\mathrm{e}\mathrm{m}\mathrm{p}\mathrm{t}\mathrm{y}}$	distance of AGV without tasks
T	the total delivery time of AGV
$T_{\mathrm{f}\mathrm{u}\mathrm{l}\mathrm{l}}$	the time used for delivering the tasks for the AGV
$T_{\mathrm{e}\mathrm{m}\mathrm{p}\mathrm{t}\mathrm{y}}$	running time of the AGV without tasks
E	the total battery consumption of AGV
$E_{\mathrm{f}\mathrm{u}\mathrm{l}\mathrm{l}}$	the battery consumption of the AGV with tasks
$E_{\mathrm{e}\mathrm{m}\mathrm{p}\mathrm{t}\mathrm{y}}$	the battery consumption of the AGV without tasks
$V_{\mathrm{f}\mathrm{u}\mathrm{l}\mathrm{l}}$	the battery consumption per unit for the AGV with tasks
$V_{\mathrm{e}\mathrm{m}\mathrm{p}\mathrm{t}\mathrm{y}}$	the battery consumption per unit for the AGV without tasks

Table A2. Position of stations in proof-of-concept prototype in a laboratory environment.

Station	$X\left(m\right)$	$Y\left(m\right)$
2	7.00	10.00
3 in	7.20	6.00
3 out	9.20	6.00
4 in	7.20	7.50
4 out	9.20	7.50
5 in	7.20	9.00
5 out	9.20	9.00
6	10.60	9.30
7	13.60	9.30
8	13.00	6.60
9	15.00	6.00
10	16.00	8.00

Table A3. Tasks for material handling in the proof-of-concept.

Cycle	Task	Task type	From station	To station	Window time start (s)	Material handling time (s)	Window time end (s)	Duration (s)
1	1	VA	(2)	(10)	0	50.00	230.00	230.00
	2	VA	(10)	(3) in	80.00	50.00	310.00	230.00
	3	NVA	(7)	(8)	0	27.00	400.00	400.00
	4	VA	(10)	(4) in	100.00	42.00	330.00	230.00
	5	VA	(10)	(5) in	100.00	37.00	330.00	230.00
2	6	VA	(3) out	(2)	400.00	30.00	630.00	230.00
	7	VA	(2)	(10)	500.00	50.00	730.00	230.00
	8	NVA	(10)	(9)	400	22.00	800.00	400.00
	9	VA	(10)	(5) in	450.00	37.00	680.00	230.00
	10	VA	(4) out	(2)	500.00	44.00	730.00	230.00
3	11	VA	(2)	(3) in	820.00	15.00	1050.00	230.00
	12	VA	(2)	(10)	800.00	50.00	1030.00	230.00
	13	NVA	(2)	(9)	800.00	35.00	1200.00	400.00
	14	VA	(10)	(3) in	850.00	50.00	1080.00	230.00
	15	VA	(10)	(4) in	950.00	42.00	1180.00	230.00
4	16	VA	(2)	(10)	1,200.00	50.00	1430.00	230.00
	17	VA	(3) out	(2)	1,350.00	30.00	1580.00	230.00
	18	NVA	(6)	(9)	1200.00	34.00	1600.00	400.00
	19	VA	(4) out	(2)	1200.00	44.00	1430.00	230.00
	20	VA	(5) out	(2)	1300.00	32.00	1530.00	230.00
5	21	VA	(10)	(3) in	1610.00	50.00	1,840.00	230.00
	22	VA	(10)	(4) in	1700.00	42.00	1930.00	230.00
	23	NVA	(7)	(8)	1600.00	27.00	2000.00	400.00
	24	VA	(10)	(5) in	1680.00	37.00	1910.00	230.00
	25	VA	(2)	(10)	1770.00	50.00	2000.00	230.00
6	26	VA	(3) out	(2)	2010.00	30.00	2,240.00	230.00
	27	VA	(4) out	(2)	2050.00	44.00	2280.00	230.00
	28	NVA	(9)	(7)	2000.00	20.00	2400.00	400.00
	29	VA	(10)	(3) in	2100.00	50.00	2330.00	230.00
	30	VA	(5) out	(2)	2100.00	32.00	2330.00	230.00
7	31	VA	(2)	(10)	2400.00	50.00	2630.00	230.00
	32	VA	(2)	(10)	2430.00	50.00	2660.00	230.00
	33	NVA	(8)	(2)	2400.00	37.00	2800.00	400.00
	34	VA	(10)	(3) in	2470.00	50.00	2700.00	230.00
	35	VA	(10)	(4) in	2570.00	42.00	2800.00	230.00
8	36	VA	(3) out	(2)	2800.00	30.00	3030.00	230.00
	37	VA	(4) out	(2)	2870.00	44.00	3100.00	230.00
	38	NVA	(6)	(7)	2800.00	27.00	3200.00	400.00
	39	VA	(3) out	(8)	2950.00	20.00	3180.00	230.00
	40	VA	(5) out	(2)	2900.00	32.00	3130.00	230.00
9	41	VA	(10)	(3) in	3200.00	50.00	3430.00	230.00
	42	VA	(10)	(5) in	3210.00	37.00	3440.00	230.00
	43	NVA	(8)	(6)	3200.00	31.00	3600.00	400.00
	44	VA	(10)	(5) in	3370.00	37.00	3600.00	230.00
	45	VA	(2)	(10)	3300.00	50.00	3530.00	230.00
10	46	VA	(10)	(4) in	3630.00	42.00	3860.00	230.00
	47	VA	(5) out	(2)	3600.00	32.00	3830.00	230.00
	48	NVA	(9)	(6)	3600.00	34.00	4000.00	400.00
	49	VA	(3) out	(2)	3700.00	30.00	3930.00	230.00
	50	VA	(4) out	(2)	3750.00	44.00	3980.00	230.00

Table A4. Optimal results of data-driven dynamic optimisation of tasks in material handling (VA: value added task, NVA: non value added task).

Cycle	Task	Task type	From station	To station	PickUp(s)	Material handling time (s)	Delivery (s)	Makespan (s)	Distance (m)	Battery consumption (W)
1	1	VA	(2)	(10)	52.00	50.00	102.00	325.00	18.16	162.50
	4	VA	(10)	(4) in	102.00	42.00	144.00
	5	VA	(10)	(5) in	186.00	37.00	223.00
	2	VA	(10)	(3) in	260.00	50.00	310.00
	3	NVA	(9)	(8)	350.00	27.00	377.00
2	6	VA	(3) out	(2)	537.00	30.00	567.00	263.00	14.69	131.50
	7	VA	(2)	(10)	567.00	50.00	617.00
	9	VA	(10)	(5) in	617.00	37.00	654.00
	10	VA	(4) out	(2)	684.00	44.00	728.00
	8	NVA	(10)	(9)	778.00	22.00	800.00
3	11	VA	(2)	(3) in	916.00	15.00	931.00	284.00	15.87	142.00
	12	VA	(2)	(10)	946.00	50.00	996.00
	14	VA	(10)	(3) in	996.00	50.00	1046.00
	15	VA	(10)	(4) in	1096.00	42.00	1138.00
	13	NVA	(2)	(9)	1165.00	35.00	1200.00
4	16	VA	(2)	(10)	1275.00	50.00	1325.00	325.00	18.16	162.50
	19	VA	(4) out	(2)	1352.00	44.00	1396.00
	17	VA	(3) out	(2)	1426.00	30.00	1456.00
	20	VA	(5) out	(2)	1488.00	32.00	1520.00
	18	NVA	(6)	(9)	1566.00	34.00	1600.00
5	21	VA	(10)	(3) in	1,650.00	50.00	1700.00	350.00	19.55	175.00
	24	VA	(10)	(5) in	1750.00	37.00	1787.00
	22	VA	(10)	(4) in	1824.00	42.00	1866.00
	25	VA	(2)	(10)	1893.00	50.00	1943.00
	23	NVA	(9)	(8)	1973.00	27.00	2000.00
6	26	VA	(3) out	(2)	2048.00	30.00	2078.00	337.00	18.16	168.50
	27	VA	(4) out	(2)	2122.00	44.00	2166.00
	29	VA	(10)	(3) in	2216.00	50.00	2266.00
	30	VA	(5) out	(2)	2298.00	32.00	2330.00
	28	NVA	(9)	(9)	2357.00	20.00	2377.00
7	31	VA	(2)	(10)	2435.00	50.00	2485.00	365.00	20.39	182.50
	32	VA	(2)	(10)	2535.00	50.00	2585.00
	34	VA	(10)	(3) in	2585.00	50.00	235.00
	35	VA	(10)	(4) in	2677.00	42.00	2719.00
	33	NVA	(8)	(2)	2763.00	37.00	2800.00
8	36	VA	(3) out	(2)	2890.00	30.00	2920.00	290.00	16.20	145.00
	37	VA	(4) out	(2)	2964.00	44.00	3008.00
	40	VA	(5) out	(2)	3040.00	32.00	3072.00
	39	VA	(3) out	(8)	3102.00	20.00	3122.00
	38	NVA	(6)	(9)	3153.00	27.00	3180.00
9	42	VA	(10)	(5) in	3306.00	37.00	3343.00	289.00	16.15	145.50
	41	VA	(10)	(3) in	3380.00	50.00	3430.00
	45	VA	(2)	(10)	3445.00	50.00	3495.00
	44	VA	(10)	(5) in	3495.00	37.00	3532.00
	43	NVA	(8)	(6)	3564.00	31.00	3595.00
10	46	VA	(10)	(4) in	3680.00	42.00	3722.00	320.00	17.88	160.00
	47	VA	(5) out	(2)	3751.00	32.00	3783.00
	49	VA	(3) out	(2)	3813.00	30.00	3843.00
	50	VA	(4) out	(2)	3887.00	44.00	3931.00
	48	NVA	(9)	(6)	3966.00	34.00	4000.00

Figure A1. Industrial Internet of Things digital servitization for smart production logistics device profile.

Architecture for Industrial Internet of Things-enabled digital servitization in smart production logistics including a sensing, networking, and applications layer.

Figure A2. Industrial Internet of Things digital servitization for smart production logistics activity profile.

A data model for multichannel communication including IIoT modeling profiles, data bases, production logistics tasks, and services.

Data availability statement

The data that support the findings of this study are available from the corresponding author, Erik Flores-García ([email protected]), upon reasonable request.