Spremembe

              
    

          
          
        
        

            
f
1
{
f
1
{
            
2
  "author": "Toby Dukes",
2
  "author": "Toby Dukes",
            
3
  "author_email": "toby.dukes@amfg.ai",
3
  "author_email": "toby.dukes@amfg.ai",
            
4
  "cloud_storage_key_segment": 
4
  "cloud_storage_key_segment": 
            
5
"smdh-amfg-predictive-tooling-maintenance",
5
"smdh-amfg-predictive-tooling-maintenance",
            
6
  "creator_user_id": "1a7e53fd-7c0f-4751-80ed-46abbbec41eb",
6
  "creator_user_id": "1a7e53fd-7c0f-4751-80ed-46abbbec41eb",
            
7
  "groups": [],
7
  "groups": [],
            
8
  "id": "b21a9006-60f7-4a45-ba1b-cbb5e99d9251",
8
  "id": "b21a9006-60f7-4a45-ba1b-cbb5e99d9251",
            
9
  "isopen": false,
9
  "isopen": false,
            
10
  "license_id": "notspecified",
10
  "license_id": "notspecified",
            
11
  "license_title": "License not specified",
11
  "license_title": "License not specified",
            
12
  "maintainer": "Toby Dukes",
12
  "maintainer": "Toby Dukes",
            
13
  "maintainer_email": "toby.dukes@amfg.ai",
13
  "maintainer_email": "toby.dukes@amfg.ai",
            
14
  "metadata_created": "2025-02-24T17:51:14.568612",
14
  "metadata_created": "2025-02-24T17:51:14.568612",
            
n
15
  "metadata_modified": "2025-02-28T10:03:59.429588",
n
15
  "metadata_modified": "2025-02-28T10:05:41.857814",
            
16
  "name": 
16
  "name": 
            
17
tonomous-manufacturing-ltd--smdh-amfg-predictive-tooling-maintenance",
17
tonomous-manufacturing-ltd--smdh-amfg-predictive-tooling-maintenance",
            
18
  "notes": "This is the data provided for each SME for the lighthouse 
18
  "notes": "This is the data provided for each SME for the lighthouse 
            
19
project Zero barrier predictive maintenance for SMEs in the machining 
19
project Zero barrier predictive maintenance for SMEs in the machining 
            
20
industry. There will be 4 separate XLS files uploaded for each of the 
20
industry. There will be 4 separate XLS files uploaded for each of the 
            
21
testbeds that were used for data collection. The data varies slightly 
21
testbeds that were used for data collection. The data varies slightly 
            
22
per testbed based on machines and tools used.",
22
per testbed based on machines and tools used.",
            
n
23
  "num_resources": 3,
n
23
  "num_resources": 4,
            
24
  "num_tags": 2,
24
  "num_tags": 2,
            
25
  "organization": {
25
  "organization": {
            
26
    "approval_status": "approved",
26
    "approval_status": "approved",
            
27
    "created": "2025-02-24T15:04:07.122089",
27
    "created": "2025-02-24T15:04:07.122089",
            
28
    "description": "",
28
    "description": "",
            
29
    "id": "f59d8904-f418-45f0-b94b-bc5980219766",
29
    "id": "f59d8904-f418-45f0-b94b-bc5980219766",
            
30
    "image_url": "",
30
    "image_url": "",
            
31
    "is_organization": true,
31
    "is_organization": true,
            
32
    "name": "autonomous-manufacturing-ltd",
32
    "name": "autonomous-manufacturing-ltd",
            
33
    "state": "active",
33
    "state": "active",
            
34
    "title": "Autonomous Manufacturing Ltd",
34
    "title": "Autonomous Manufacturing Ltd",
            
35
    "type": "organization"
35
    "type": "organization"
            
36
  },
36
  },
            
37
  "owner_org": "f59d8904-f418-45f0-b94b-bc5980219766",
37
  "owner_org": "f59d8904-f418-45f0-b94b-bc5980219766",
            
38
  "private": false,
38
  "private": false,
            
39
  "relationships_as_object": [],
39
  "relationships_as_object": [],
            
40
  "relationships_as_subject": [],
40
  "relationships_as_subject": [],
            
41
  "resources": [
41
  "resources": [
            
42
    {
42
    {
            
43
      "cache_last_updated": null,
43
      "cache_last_updated": null,
            
44
      "cache_url": null,
44
      "cache_url": null,
            
45
      "cloud_storage_key": 
45
      "cloud_storage_key": 
            
46
nomous-manufacturing-ltd/smdh-amfg-predictive-tooling-maintenance/SME1 
46
nomous-manufacturing-ltd/smdh-amfg-predictive-tooling-maintenance/SME1 
            
47
Tooling data.",
47
Tooling data.",
            
48
      "created": "2025-02-24T17:53:19.676938",
48
      "created": "2025-02-24T17:53:19.676938",
            
49
      "datastore_active": false,
49
      "datastore_active": false,
            
50
      "description": "Data for the SME1 - including parts created, 
50
      "description": "Data for the SME1 - including parts created, 
            
51
tools / machines used. part geometry and tooling information. \r\nSME 
51
tools / machines used. part geometry and tooling information. \r\nSME 
            
52
creates small, bespoke parts.",
52
creates small, bespoke parts.",
            
53
      "format": "XLSX",
53
      "format": "XLSX",
            
54
      "hash": "",
54
      "hash": "",
            
55
      "id": "9153bbd8-cbeb-4c36-84eb-946eb2ec0b79",
55
      "id": "9153bbd8-cbeb-4c36-84eb-946eb2ec0b79",
            
56
      "last_modified": null,
56
      "last_modified": null,
            
57
      "metadata_modified": "2025-02-24T17:53:23.382418",
57
      "metadata_modified": "2025-02-24T17:53:23.382418",
            
58
      "mimetype": null,
58
      "mimetype": null,
            
59
      "mimetype_inner": null,
59
      "mimetype_inner": null,
            
60
      "name": "SME1 Tooling data.",
60
      "name": "SME1 Tooling data.",
            
61
      "package_id": "b21a9006-60f7-4a45-ba1b-cbb5e99d9251",
61
      "package_id": "b21a9006-60f7-4a45-ba1b-cbb5e99d9251",
            
62
      "position": 0,
62
      "position": 0,
            
63
      "resource_type": null,
63
      "resource_type": null,
            
64
      "size": 126831,
64
      "size": 126831,
            
65
      "state": "active",
65
      "state": "active",
            
66
      "tags": "Method-Machine_learning",
66
      "tags": "Method-Machine_learning",
            
67
      "url": 
67
      "url": 
            
68
ce/9153bbd8-cbeb-4c36-84eb-946eb2ec0b79/download/sme1_smdh_data.xlsx",
68
ce/9153bbd8-cbeb-4c36-84eb-946eb2ec0b79/download/sme1_smdh_data.xlsx",
            
69
      "url_type": "upload"
69
      "url_type": "upload"
            
70
    },
70
    },
            
71
    {
71
    {
            
72
      "cache_last_updated": null,
72
      "cache_last_updated": null,
            
73
      "cache_url": null,
73
      "cache_url": null,
            
74
      "cloud_storage_key": 
74
      "cloud_storage_key": 
            
75
nomous-manufacturing-ltd/smdh-amfg-predictive-tooling-maintenance/SME2 
75
nomous-manufacturing-ltd/smdh-amfg-predictive-tooling-maintenance/SME2 
            
76
Tooling Data",
76
Tooling Data",
            
77
      "created": "2025-02-25T12:21:44.983320",
77
      "created": "2025-02-25T12:21:44.983320",
            
78
      "datastore_active": false,
78
      "datastore_active": false,
            
79
      "description": "Tooling Data capture from SME2 Shows part pass / 
79
      "description": "Tooling Data capture from SME2 Shows part pass / 
            
80
failure rate based on the expected v actual tool life calculation.",
80
failure rate based on the expected v actual tool life calculation.",
            
81
      "format": ".xlsx",
81
      "format": ".xlsx",
            
82
      "hash": "",
82
      "hash": "",
            
83
      "id": "f87a6ccb-aa38-42e0-bb4f-8f37c7cfe8c7",
83
      "id": "f87a6ccb-aa38-42e0-bb4f-8f37c7cfe8c7",
            
84
      "last_modified": null,
84
      "last_modified": null,
            
85
      "metadata_modified": "2025-02-25T12:22:52.666260",
85
      "metadata_modified": "2025-02-25T12:22:52.666260",
            
86
      "mimetype": null,
86
      "mimetype": null,
            
87
      "mimetype_inner": null,
87
      "mimetype_inner": null,
            
88
      "name": "SME2 Tooling Data",
88
      "name": "SME2 Tooling Data",
            
89
      "package_id": "b21a9006-60f7-4a45-ba1b-cbb5e99d9251",
89
      "package_id": "b21a9006-60f7-4a45-ba1b-cbb5e99d9251",
            
90
      "position": 1,
90
      "position": 1,
            
91
      "resource_type": null,
91
      "resource_type": null,
            
92
      "size": 994904,
92
      "size": 994904,
            
93
      "state": "active",
93
      "state": "active",
            
94
      "tags": "Method-Machine_learning",
94
      "tags": "Method-Machine_learning",
            
95
      "url": 
95
      "url": 
            
96
ce/f87a6ccb-aa38-42e0-bb4f-8f37c7cfe8c7/download/sme2_smdh_data.xlsx",
96
ce/f87a6ccb-aa38-42e0-bb4f-8f37c7cfe8c7/download/sme2_smdh_data.xlsx",
            
97
      "url_type": "upload"
97
      "url_type": "upload"
            
98
    },
98
    },
            
99
    {
99
    {
            
100
      "cache_last_updated": null,
100
      "cache_last_updated": null,
            
101
      "cache_url": null,
101
      "cache_url": null,
            
102
      "cloud_storage_key": 
102
      "cloud_storage_key": 
            
103
nomous-manufacturing-ltd/smdh-amfg-predictive-tooling-maintenance/SME3 
103
nomous-manufacturing-ltd/smdh-amfg-predictive-tooling-maintenance/SME3 
            
104
Tooling Data",
104
Tooling Data",
            
105
      "created": "2025-02-27T12:08:47.094294",
105
      "created": "2025-02-27T12:08:47.094294",
            
106
      "datastore_active": false,
106
      "datastore_active": false,
            
107
      "description": "Tooling and part failure rate for SME3 ",
107
      "description": "Tooling and part failure rate for SME3 ",
            
108
      "format": "XLSX",
108
      "format": "XLSX",
            
109
      "hash": "",
109
      "hash": "",
            
110
      "id": "91e645df-a6c6-471a-934f-baa3c23de09f",
110
      "id": "91e645df-a6c6-471a-934f-baa3c23de09f",
            
111
      "last_modified": null,
111
      "last_modified": null,
            
112
      "metadata_modified": "2025-02-27T12:08:56.205082",
112
      "metadata_modified": "2025-02-27T12:08:56.205082",
            
113
      "mimetype": null,
113
      "mimetype": null,
            
114
      "mimetype_inner": null,
114
      "mimetype_inner": null,
            
115
      "name": "SME3 Tooling Data",
115
      "name": "SME3 Tooling Data",
            
116
      "package_id": "b21a9006-60f7-4a45-ba1b-cbb5e99d9251",
116
      "package_id": "b21a9006-60f7-4a45-ba1b-cbb5e99d9251",
            
117
      "position": 2,
117
      "position": 2,
            
118
      "resource_type": null,
118
      "resource_type": null,
            
119
      "size": 369715,
119
      "size": 369715,
            
120
      "state": "active",
120
      "state": "active",
            
121
      "tags": "Method-Machine_learning",
121
      "tags": "Method-Machine_learning",
            
122
      "url": 
122
      "url": 
            
123
91e645df-a6c6-471a-934f-baa3c23de09f/download/sme3-tooling-data.xlsx",
123
91e645df-a6c6-471a-934f-baa3c23de09f/download/sme3-tooling-data.xlsx",
            
124
      "url_type": "upload"
124
      "url_type": "upload"
            
n
n
125
    },
            
126
    {
            
127
      "cache_last_updated": null,
            
128
      "cache_url": null,
            
129
      "cloud_storage_key": 
            
130
ing-ltd/smdh-amfg-predictive-tooling-maintenance/SME4_Part_Data.xlsx",
            
131
      "created": "2025-02-28T10:05:41.870730",
            
132
      "datastore_active": false,
            
133
      "description": "Tooling data for SME4 including part level data, 
            
134
machine level data and tool level data, resulting in a part pass / 
            
135
fail based on tool life remaining compared to maintenance 
            
136
prediction.",
            
137
      "format": "XLSX",
            
138
      "hash": "",
            
139
      "id": "954e6d43-b16f-46ae-9074-24257c15871e",
            
140
      "last_modified": null,
            
141
      "metadata_modified": "2025-02-28T10:05:41.861959",
            
142
      "mimetype": null,
            
143
      "mimetype_inner": null,
            
144
      "name": "SME4_Part_Data.xlsx",
            
145
      "package_id": "b21a9006-60f7-4a45-ba1b-cbb5e99d9251",
            
146
      "position": 3,
            
147
      "resource_type": null,
            
148
      "size": 1297584,
            
149
      "state": "active",
            
150
      "tags": "Method-Machine_learning",
            
151
      "url": 
            
152
/954e6d43-b16f-46ae-9074-24257c15871e/download/sme4_part_data-1.xlsx",
            
153
      "url_type": "upload"
            
125
    }
154
    }
            
126
  ],
155
  ],
            
127
  "share_internally": true,
156
  "share_internally": true,
            
128
  "state": "active",
157
  "state": "active",
            
129
  "tags": [
158
  "tags": [
            
130
    {
159
    {
            
131
      "display_name": "Method-Machine_learning",
160
      "display_name": "Method-Machine_learning",
            
132
      "id": "1e5e8aa0-953c-4432-b042-505a9be6e22c",
161
      "id": "1e5e8aa0-953c-4432-b042-505a9be6e22c",
            
133
      "name": "Method-Machine_learning",
162
      "name": "Method-Machine_learning",
            
134
      "state": "active",
163
      "state": "active",
            
135
      "vocabulary_id": "55a807af-3944-4bf2-b2d8-585c8b1b8e04"
164
      "vocabulary_id": "55a807af-3944-4bf2-b2d8-585c8b1b8e04"
            
136
    },
165
    },
            
137
    {
166
    {
            
138
      "display_name": "Method-Machine_learning",
167
      "display_name": "Method-Machine_learning",
            
139
      "id": "dc7d30cc-966f-4eaa-8485-3c86b7413c3d",
168
      "id": "dc7d30cc-966f-4eaa-8485-3c86b7413c3d",
            
140
      "name": "Method-Machine_learning",
169
      "name": "Method-Machine_learning",
            
141
      "state": "active",
170
      "state": "active",
            
142
      "vocabulary_id": null
171
      "vocabulary_id": null
            
143
    },
172
    },
            
144
    {
173
    {
            
145
      "name": "Method-Machine_learning",
174
      "name": "Method-Machine_learning",
            
146
      "vocabulary_id": "55a807af-3944-4bf2-b2d8-585c8b1b8e04"
175
      "vocabulary_id": "55a807af-3944-4bf2-b2d8-585c8b1b8e04"
            
147
    },
176
    },
            
148
    {
177
    {
            
149
      "name": "Method-Machine_learning",
178
      "name": "Method-Machine_learning",
            
150
      "vocabulary_id": "55a807af-3944-4bf2-b2d8-585c8b1b8e04"
179
      "vocabulary_id": "55a807af-3944-4bf2-b2d8-585c8b1b8e04"
            
151
    },
180
    },
            
152
    {
181
    {
            
153
      "name": "Method-Machine_learning",
182
      "name": "Method-Machine_learning",
            
154
      "vocabulary_id": "55a807af-3944-4bf2-b2d8-585c8b1b8e04"
183
      "vocabulary_id": "55a807af-3944-4bf2-b2d8-585c8b1b8e04"
            
t
t
184
    },
            
185
    {
            
186
      "name": "Method-Machine_learning",
            
187
      "vocabulary_id": "55a807af-3944-4bf2-b2d8-585c8b1b8e04"
            
155
    }
188
    }
            
156
  ],
189
  ],
            
157
  "title": "SMDH / AMFG predictive tooling maintenance",
190
  "title": "SMDH / AMFG predictive tooling maintenance",
            
158
  "type": "dataset",
191
  "type": "dataset",
            
159
  "url": "",
192
  "url": "",
            
160
  "version": "1.0"
193
  "version": "1.0"
            
161
}
194
}