{"id":6615,"date":"2026-02-05T14:11:13","date_gmt":"2026-02-05T06:11:13","guid":{"rendered":"https:\/\/en.siasun.com\/?p=6615"},"modified":"2026-03-04T09:53:14","modified_gmt":"2026-03-04T01:53:14","slug":"mobile-robot-statistical-analysis-system","status":"publish","type":"post","link":"https:\/\/en.siasun.com\/th\/mobile-robot-statistical-analysis-system.html","title":{"rendered":"\u0e23\u0e30\u0e1a\u0e1a\u0e01\u0e32\u0e23\u0e27\u0e34\u0e40\u0e04\u0e23\u0e32\u0e30\u0e2b\u0e4c\u0e17\u0e32\u0e07\u0e2a\u0e16\u0e34\u0e15\u0e34\u0e02\u0e2d\u0e07\u0e2b\u0e38\u0e48\u0e19\u0e22\u0e19\u0e15\u0e4c\u0e40\u0e04\u0e25\u0e37\u0e48\u0e2d\u0e19\u0e17\u0e35\u0e48"},"content":{"rendered":"
\n
\n

\u0e28\u0e39\u0e19\u0e22\u0e4c\u0e01\u0e25\u0e32\u0e07\u0e1c\u0e25\u0e34\u0e15\u0e20\u0e31\u0e13\u0e11\u0e4c<\/h2>\n\n\n\n

<\/p>\n<\/div>\n<\/div>

<\/div>
<\/div>
<\/div><\/div><\/section>\n\n\n\n
\u0e1a\u0e17\u0e19\u0e33<\/a><\/a><\/div>
\u0e02\u0e49\u0e2d\u0e14\u0e35<\/a><\/a><\/div>
\u0e1e\u0e37\u0e49\u0e19\u0e17\u0e35\u0e48\u0e01\u0e32\u0e23\u0e43\u0e0a\u0e49\u0e07\u0e32\u0e19<\/a><\/a><\/div>
\u0e1e\u0e32\u0e23\u0e32\u0e21\u0e34\u0e40\u0e15\u0e2d\u0e23\u0e4c<\/a><\/a><\/div>
\u0e01\u0e23\u0e13\u0e35\u0e28\u0e36\u0e01\u0e29\u0e32<\/a><\/a><\/div><\/div><\/div><\/div>\n\n\n\n
\n
\n
\"\u0e2b\u0e38\u0e48\u0e19\u0e22\u0e19\u0e15\u0e4c\u0e40\u0e04\u0e25\u0e37\u0e48\u0e2d\u0e19\u0e17\u0e35\u0e48\u0e41\u0e1a\u0e1a\u0e23\u0e16\u0e22\u0e01\"\/<\/a><\/div><\/div>
\n
\n
<\/div><\/div>\n\n\n\n
\n
\n

\u0e23\u0e30\u0e1a\u0e1a\u0e01\u0e32\u0e23\u0e27\u0e34\u0e40\u0e04\u0e23\u0e32\u0e30\u0e2b\u0e4c\u0e17\u0e32\u0e07\u0e2a\u0e16\u0e34\u0e15\u0e34\u0e02\u0e2d\u0e07\u0e2b\u0e38\u0e48\u0e19\u0e22\u0e19\u0e15\u0e4c\u0e40\u0e04\u0e25\u0e37\u0e48\u0e2d\u0e19\u0e17\u0e35\u0e48<\/strong><\/h1>\n\n\n\n

<\/p>\n\n\n\n

\n
\n

\u0e23\u0e30\u0e1a\u0e1a\u0e27\u0e34\u0e40\u0e04\u0e23\u0e32\u0e30\u0e2b\u0e4c\u0e2a\u0e16\u0e34\u0e15\u0e34\u0e2b\u0e38\u0e48\u0e19\u0e22\u0e19\u0e15\u0e4c\u0e40\u0e04\u0e25\u0e37\u0e48\u0e2d\u0e19\u0e17\u0e35\u0e48 (Mobile Robot Statistical Analysis System) \u0e16\u0e39\u0e01\u0e1e\u0e31\u0e12\u0e19\u0e32\u0e02\u0e36\u0e49\u0e19\u0e1a\u0e19\u0e04\u0e25\u0e31\u0e07\u0e02\u0e49\u0e2d\u0e21\u0e39\u0e25 IMRS (IMRS data lake) \u0e0b\u0e36\u0e48\u0e07\u0e43\u0e2b\u0e49\u0e1a\u0e23\u0e34\u0e01\u0e32\u0e23\u0e01\u0e32\u0e23\u0e23\u0e27\u0e1a\u0e23\u0e27\u0e21\u0e02\u0e49\u0e2d\u0e21\u0e39\u0e25\u0e2b\u0e25\u0e32\u0e22\u0e21\u0e34\u0e15\u0e34\u0e41\u0e25\u0e30\u0e01\u0e32\u0e23\u0e27\u0e34\u0e40\u0e04\u0e23\u0e32\u0e30\u0e2b\u0e4c\u0e02\u0e49\u0e2d\u0e21\u0e39\u0e25\u0e40\u0e0a\u0e34\u0e07\u0e20\u0e32\u0e1e\u0e2a\u0e33\u0e2b\u0e23\u0e31\u0e1a\u0e01\u0e25\u0e38\u0e48\u0e21\u0e2b\u0e38\u0e48\u0e19\u0e22\u0e19\u0e15\u0e4c\u0e40\u0e04\u0e25\u0e37\u0e48\u0e2d\u0e19\u0e17\u0e35\u0e48 \u0e23\u0e30\u0e1a\u0e1a\u0e19\u0e35\u0e49\u0e23\u0e27\u0e1a\u0e23\u0e27\u0e21\u0e02\u0e49\u0e2d\u0e21\u0e39\u0e25\u0e2a\u0e16\u0e32\u0e19\u0e30\u0e02\u0e2d\u0e07\u0e2b\u0e38\u0e48\u0e19\u0e22\u0e19\u0e15\u0e4c\u0e41\u0e1a\u0e1a\u0e40\u0e23\u0e35\u0e22\u0e25\u0e44\u0e17\u0e21\u0e4c \u0e01\u0e32\u0e23\u0e14\u0e33\u0e40\u0e19\u0e34\u0e19\u0e01\u0e32\u0e23\u0e15\u0e32\u0e21\u0e20\u0e32\u0e23\u0e01\u0e34\u0e08 \u0e41\u0e25\u0e30\u0e02\u0e49\u0e2d\u0e21\u0e39\u0e25\u0e2a\u0e38\u0e02\u0e20\u0e32\u0e1e\u0e02\u0e2d\u0e07\u0e2d\u0e38\u0e1b\u0e01\u0e23\u0e13\u0e4c \u0e41\u0e25\u0e30\u0e19\u0e33\u0e40\u0e2a\u0e19\u0e2d\u0e02\u0e49\u0e2d\u0e21\u0e39\u0e25\u0e40\u0e0a\u0e34\u0e07\u0e25\u0e36\u0e01\u0e1c\u0e48\u0e32\u0e19\u0e41\u0e14\u0e0a\u0e1a\u0e2d\u0e23\u0e4c\u0e14\u0e41\u0e25\u0e30\u0e23\u0e32\u0e22\u0e07\u0e32\u0e19\u0e17\u0e35\u0e48\u0e1b\u0e23\u0e31\u0e1a\u0e41\u0e15\u0e48\u0e07\u0e15\u0e32\u0e21\u0e04\u0e27\u0e32\u0e21\u0e15\u0e49\u0e2d\u0e07\u0e01\u0e32\u0e23\u0e02\u0e2d\u0e07\u0e1c\u0e39\u0e49\u0e43\u0e0a\u0e49 \u0e14\u0e49\u0e27\u0e22\u0e01\u0e32\u0e23\u0e27\u0e34\u0e40\u0e04\u0e23\u0e32\u0e30\u0e2b\u0e4c\u0e02\u0e49\u0e2d\u0e21\u0e39\u0e25\u0e02\u0e19\u0e32\u0e14\u0e43\u0e2b\u0e0d\u0e48 (big-data analytics) \u0e23\u0e30\u0e1a\u0e1a\u0e19\u0e35\u0e49\u0e0a\u0e48\u0e27\u0e22\u0e2a\u0e19\u0e31\u0e1a\u0e2a\u0e19\u0e38\u0e19\u0e01\u0e32\u0e23\u0e15\u0e31\u0e14\u0e2a\u0e34\u0e19\u0e43\u0e08\u0e2d\u0e22\u0e48\u0e32\u0e07\u0e0a\u0e32\u0e0d\u0e09\u0e25\u0e32\u0e14\u0e40\u0e1e\u0e37\u0e48\u0e2d\u0e01\u0e32\u0e23\u0e1b\u0e23\u0e31\u0e1a\u0e1b\u0e23\u0e38\u0e07\u0e40\u0e2a\u0e49\u0e19\u0e17\u0e32\u0e07\u0e01\u0e32\u0e23\u0e17\u0e33\u0e07\u0e32\u0e19 \u0e01\u0e32\u0e23\u0e08\u0e31\u0e14\u0e2a\u0e23\u0e23\u0e20\u0e32\u0e23\u0e01\u0e34\u0e08\u0e2d\u0e22\u0e48\u0e32\u0e07\u0e21\u0e35\u0e1b\u0e23\u0e30\u0e2a\u0e34\u0e17\u0e18\u0e34\u0e20\u0e32\u0e1e \u0e41\u0e25\u0e30\u0e01\u0e32\u0e23\u0e1b\u0e23\u0e31\u0e1a\u0e1b\u0e23\u0e38\u0e07 takt \u0e02\u0e2d\u0e07\u0e01\u0e32\u0e23\u0e1c\u0e25\u0e34\u0e15 \u0e15\u0e25\u0e2d\u0e14\u0e08\u0e19\u0e0a\u0e48\u0e27\u0e22\u0e43\u0e2b\u0e49\u0e2a\u0e32\u0e21\u0e32\u0e23\u0e16\u0e17\u0e33\u0e19\u0e32\u0e22\u0e01\u0e32\u0e23\u0e1a\u0e33\u0e23\u0e38\u0e07\u0e23\u0e31\u0e01\u0e29\u0e32\u0e40\u0e1e\u0e37\u0e48\u0e2d\u0e25\u0e14\u0e04\u0e27\u0e32\u0e21\u0e40\u0e2a\u0e35\u0e48\u0e22\u0e07\u0e02\u0e2d\u0e07\u0e01\u0e32\u0e23\u0e2b\u0e22\u0e38\u0e14\u0e17\u0e33\u0e07\u0e32\u0e19\u0e17\u0e35\u0e48\u0e44\u0e21\u0e48\u0e04\u0e32\u0e14\u0e04\u0e34\u0e14.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

<\/p>\n\n\n\n

\"\u0e2b\u0e38\u0e48\u0e19\u0e22\u0e19\u0e15\u0e4c\u0e40\u0e04\u0e25\u0e37\u0e48\u0e2d\u0e19\u0e17\u0e35\u0e48+\u0e23\u0e30\u0e1a\u0e1a\u0e41\u0e25\u0e30\u0e42\u0e0b\u0e25\u0e39\u0e0a\u0e31\u0e19\"\/<\/div>\u0e2b\u0e38\u0e48\u0e19\u0e22\u0e19\u0e15\u0e4c\u0e40\u0e04\u0e25\u0e37\u0e48\u0e2d\u0e19\u0e17\u0e35\u0e48+\u0e23\u0e30\u0e1a\u0e1a\u0e41\u0e25\u0e30\u0e42\u0e0b\u0e25\u0e39\u0e0a\u0e31\u0e19<\/span><\/a>
\u0e14\u0e32\u0e27\u0e19\u0e4c\u0e42\u0e2b\u0e25\u0e14<\/a><\/div><\/div><\/div>\n<\/div>\n<\/div><\/div>\n\n\n\n
\n
\n
<\/div><\/div>\n\n\n\n

\u0e02\u0e49\u0e2d\u0e14\u0e35<\/h2>\n<\/div>\n<\/div>\n\n\n\n
\n
\n
\"\u0e01\u0e32\u0e23\u0e40\u0e01\u0e47\u0e1a\u0e02\u0e49\u0e2d\u0e21\u0e39\u0e25\u0e41\u0e25\u0e30\u0e01\u0e32\u0e23\u0e41\u0e2a\u0e14\u0e07\u0e1c\u0e25\u0e02\u0e49\u0e2d\u0e21\u0e39\u0e25\"<\/div>\u0e01\u0e32\u0e23\u0e40\u0e01\u0e47\u0e1a\u0e02\u0e49\u0e2d\u0e21\u0e39\u0e25\u0e41\u0e25\u0e30\u0e01\u0e32\u0e23\u0e41\u0e2a\u0e14\u0e07\u0e1c\u0e25\u0e02\u0e49\u0e2d\u0e21\u0e39\u0e25<\/b><\/div>
\u0e2a\u0e16\u0e32\u0e19\u0e30, \u0e07\u0e32\u0e19, \u0e41\u0e25\u0e30\u0e2a\u0e38\u0e02\u0e20\u0e32\u0e1e\u0e43\u0e19\u0e17\u0e35\u0e48\u0e40\u0e14\u0e35\u0e22\u0e27<\/span><\/div>
<\/div><\/a>
\"\u0e23\u0e32\u0e22\u0e07\u0e32\u0e19\u0e2b\u0e25\u0e32\u0e22\u0e21\u0e34\u0e15\u0e34\"<\/div>\u0e23\u0e32\u0e22\u0e07\u0e32\u0e19\u0e2b\u0e25\u0e32\u0e22\u0e21\u0e34\u0e15\u0e34<\/b><\/div>
\u0e01\u0e23\u0e30\u0e1a\u0e27\u0e19\u0e01\u0e32\u0e23, \u0e2d\u0e38\u0e1b\u0e01\u0e23\u0e13\u0e4c, \u0e07\u0e32\u0e19, \u0e41\u0e25\u0e30\u0e15\u0e31\u0e27\u0e0a\u0e35\u0e49\u0e27\u0e31\u0e14\u0e1e\u0e25\u0e31\u0e07\u0e07\u0e32\u0e19<\/span><\/div>
<\/div><\/a>
\"\u0e01\u0e32\u0e23\u0e27\u0e34\u0e40\u0e04\u0e23\u0e32\u0e30\u0e2b\u0e4c\u0e40\u0e1e\u0e37\u0e48\u0e2d\u0e01\u0e32\u0e23\u0e2a\u0e19\u0e31\u0e1a\u0e2a\u0e19\u0e38\u0e19\u0e01\u0e32\u0e23\u0e15\u0e31\u0e14\u0e2a\u0e34\u0e19\u0e43\u0e08\"<\/div>\u0e01\u0e32\u0e23\u0e27\u0e34\u0e40\u0e04\u0e23\u0e32\u0e30\u0e2b\u0e4c\u0e40\u0e1e\u0e37\u0e48\u0e2d\u0e01\u0e32\u0e23\u0e2a\u0e19\u0e31\u0e1a\u0e2a\u0e19\u0e38\u0e19\u0e01\u0e32\u0e23\u0e15\u0e31\u0e14\u0e2a\u0e34\u0e19\u0e43\u0e08<\/b><\/div>
\u0e40\u0e1e\u0e34\u0e48\u0e21\u0e1b\u0e23\u0e30\u0e2a\u0e34\u0e17\u0e18\u0e34\u0e20\u0e32\u0e1e\u0e40\u0e2a\u0e49\u0e19\u0e17\u0e32\u0e07 \u0e01\u0e32\u0e23\u0e08\u0e31\u0e14\u0e2a\u0e48\u0e07 \u0e41\u0e25\u0e30\u0e40\u0e27\u0e25\u0e32 takt<\/span><\/div>
<\/div><\/a>
\"\u0e01\u0e32\u0e23\u0e1a\u0e33\u0e23\u0e38\u0e07\u0e23\u0e31\u0e01\u0e29\u0e32\u0e40\u0e0a\u0e34\u0e07\u0e04\u0e32\u0e14\u0e01\u0e32\u0e23\u0e13\u0e4c\"<\/div>\u0e01\u0e32\u0e23\u0e1a\u0e33\u0e23\u0e38\u0e07\u0e23\u0e31\u0e01\u0e29\u0e32\u0e40\u0e0a\u0e34\u0e07\u0e04\u0e32\u0e14\u0e01\u0e32\u0e23\u0e13\u0e4c<\/b><\/div>
\u0e04\u0e32\u0e14\u0e01\u0e32\u0e23\u0e13\u0e4c\u0e41\u0e19\u0e27\u0e42\u0e19\u0e49\u0e21\u0e2a\u0e38\u0e02\u0e20\u0e32\u0e1e\u0e41\u0e25\u0e30\u0e25\u0e14\u0e40\u0e27\u0e25\u0e32\u0e2b\u0e22\u0e38\u0e14\u0e17\u0e33\u0e07\u0e32\u0e19<\/span><\/div>
<\/div><\/a><\/div><\/div><\/section>\n<\/div>\n<\/div>
<\/div><\/section>\n\n\n\n
\n
\n
\n
\n
<\/div><\/div>\n<\/div>\n\n\n\n
\n
<\/div><\/div>\n\n\n\n

\u0e01\u0e23\u0e13\u0e35\u0e28\u0e36\u0e01\u0e29\u0e32<\/strong><\/strong><\/h2>\n<\/div>\n<\/div>\n\n\n\n

<\/p>\n\n\n\n

\n
\"\u0e01\u0e32\u0e23\u0e02\u0e22\u0e32\u0e22\u0e15\u0e31\u0e27\u0e43\u0e19\u0e15\u0e48\u0e32\u0e07\u0e1b\u0e23\u0e30\u0e40\u0e17\u0e28\u0e2d\u0e22\u0e48\u0e32\u0e07\u0e21\u0e35\u0e19\u0e31\u0e22\u0e2a\u0e33\u0e04\u0e31\u0e0d!<\/a>

\u0e01\u0e32\u0e23\u0e02\u0e22\u0e32\u0e22\u0e15\u0e31\u0e27\u0e43\u0e19\u0e15\u0e48\u0e32\u0e07\u0e1b\u0e23\u0e30\u0e40\u0e17\u0e28\u0e2d\u0e22\u0e48\u0e32\u0e07\u0e21\u0e35\u0e19\u0e31\u0e22\u0e2a\u0e33\u0e04\u0e31\u0e0d! \u0e2b\u0e38\u0e48\u0e19\u0e22\u0e19\u0e15\u0e4c\u0e40\u0e04\u0e25\u0e37\u0e48\u0e2d\u0e19\u0e17\u0e35\u0e48 SIASUN \u0e40\u0e02\u0e49\u0e32\u0e2a\u0e39\u0e48\u0e15\u0e25\u0e32\u0e14\u0e1e\u0e25\u0e31\u0e07\u0e07\u0e32\u0e19\u0e43\u0e2b\u0e21\u0e48\u0e43\u0e19\u0e22\u0e38\u0e42\u0e23\u0e1b\u0e43\u0e19\u0e1b\u0e23\u0e34\u0e21\u0e32\u0e13\u0e21\u0e32\u0e01<\/a><\/h3><\/div><\/div>
\"\u0e2d\u0e30\u0e44\u0e23\u0e17\u0e35\u0e48\u0e17\u0e33\u0e43\u0e2b\u0e49\u0e2b\u0e38\u0e48\u0e19\u0e22\u0e19\u0e15\u0e4c\u0e40\u0e04\u0e25\u0e37\u0e48\u0e2d\u0e19\u0e17\u0e35\u0e48<\/a>

\u0e2d\u0e30\u0e44\u0e23\u0e04\u0e37\u0e2d\u0e2a\u0e34\u0e48\u0e07\u0e17\u0e35\u0e48\u0e17\u0e33\u0e43\u0e2b\u0e49\u0e2b\u0e38\u0e48\u0e19\u0e22\u0e19\u0e15\u0e4c\u0e40\u0e04\u0e25\u0e37\u0e48\u0e2d\u0e19\u0e17\u0e35\u0e48 SIASUN \u0e40\u0e1b\u0e47\u0e19\u0e15\u0e31\u0e27\u0e40\u0e25\u0e37\u0e2d\u0e01\u0e2d\u0e31\u0e19\u0e14\u0e31\u0e1a\u0e2b\u0e19\u0e36\u0e48\u0e07\u0e2a\u0e33\u0e2b\u0e23\u0e31\u0e1a\u0e17\u0e31\u0e49\u0e07\u0e22\u0e31\u0e01\u0e29\u0e4c\u0e43\u0e2b\u0e0d\u0e48\u0e14\u0e49\u0e32\u0e19\u0e1e\u0e25\u0e31\u0e07\u0e07\u0e32\u0e19\u0e43\u0e2b\u0e21\u0e48\u0e23\u0e30\u0e14\u0e31\u0e1a\u0e42\u0e25\u0e01\u0e41\u0e25\u0e30\u0e41\u0e1a\u0e23\u0e19\u0e14\u0e4c\u0e23\u0e16\u0e22\u0e19\u0e15\u0e4c\u0e17\u0e35\u0e48\u0e21\u0e35\u0e1b\u0e23\u0e30\u0e27\u0e31\u0e15\u0e34\u0e22\u0e32\u0e27\u0e19\u0e32\u0e19\u0e19\u0e31\u0e1a\u0e28\u0e15\u0e27\u0e23\u0e23\u0e29?<\/a><\/h3><\/div><\/div>
\"\u0e04\u0e27\u0e32\u0e21\u0e40\u0e0a\u0e35\u0e48\u0e22\u0e27\u0e0a\u0e32\u0e0d\u0e14\u0e49\u0e32\u0e19\u0e01\u0e32\u0e23\u0e1c\u0e25\u0e34\u0e15\u0e2d\u0e31\u0e08\u0e09\u0e23\u0e34\u0e22\u0e30\u0e02\u0e2d\u0e07<\/a>

\u0e04\u0e27\u0e32\u0e21\u0e40\u0e0a\u0e35\u0e48\u0e22\u0e27\u0e0a\u0e32\u0e0d\u0e14\u0e49\u0e32\u0e19\u0e01\u0e32\u0e23\u0e1c\u0e25\u0e34\u0e15\u0e2d\u0e31\u0e08\u0e09\u0e23\u0e34\u0e22\u0e30\u0e02\u0e2d\u0e07\u0e2b\u0e38\u0e48\u0e19\u0e22\u0e19\u0e15\u0e4c\u0e40\u0e04\u0e25\u0e37\u0e48\u0e2d\u0e19\u0e17\u0e35\u0e48\u0e19\u0e49\u0e33\u0e2b\u0e19\u0e31\u0e01\u0e21\u0e32\u0e01 SIASUN<\/a><\/h3><\/div><\/div>
\"\u0e42\u0e0b\u0e25\u0e39\u0e0a\u0e31\u0e19\u0e2b\u0e38\u0e48\u0e19\u0e22\u0e19\u0e15\u0e4c\u0e40\u0e04\u0e25\u0e37\u0e48\u0e2d\u0e19\u0e17\u0e35\u0e48\u0e2a\u0e33\u0e2b\u0e23\u0e31\u0e1a\u0e2d\u0e38\u0e15\u0e2a\u0e32\u0e2b\u0e01\u0e23\u0e23\u0e21\u0e25\u0e34\u0e40\u0e18\u0e35\u0e22\u0e21\"<\/a>

\u0e42\u0e0b\u0e25\u0e39\u0e0a\u0e31\u0e19\u0e2b\u0e38\u0e48\u0e19\u0e22\u0e19\u0e15\u0e4c\u0e40\u0e04\u0e25\u0e37\u0e48\u0e2d\u0e19\u0e17\u0e35\u0e48\u0e2a\u0e33\u0e2b\u0e23\u0e31\u0e1a\u0e2d\u0e38\u0e15\u0e2a\u0e32\u0e2b\u0e01\u0e23\u0e23\u0e21\u0e25\u0e34\u0e40\u0e18\u0e35\u0e22\u0e21<\/a><\/h3><\/div><\/div>
\"\u0e0a\u0e38\u0e14\u0e1b\u0e23\u0e30\u0e01\u0e2d\u0e1a\u0e23\u0e30\u0e1a\u0e1a\u0e01\u0e31\u0e19\u0e2a\u0e30\u0e40\u0e17\u0e37\u0e2d\u0e19\u0e2b\u0e19\u0e49\u0e32\u0e41\u0e25\u0e30\u0e2b\u0e25\u0e31\u0e07<\/a>

\u0e0a\u0e38\u0e14\u0e1b\u0e23\u0e30\u0e01\u0e2d\u0e1a\u0e23\u0e30\u0e1a\u0e1a\u0e01\u0e31\u0e19\u0e2a\u0e30\u0e40\u0e17\u0e37\u0e2d\u0e19\u0e2b\u0e19\u0e49\u0e32\u0e41\u0e25\u0e30\u0e2b\u0e25\u0e31\u0e07 \u0e2a\u0e33\u0e2b\u0e23\u0e31\u0e1a\u0e15\u0e34\u0e14\u0e15\u0e31\u0e49\u0e07\u0e1a\u0e19\u0e41\u0e0a\u0e2a\u0e0b\u0e35 \u0e2b\u0e38\u0e48\u0e19\u0e22\u0e19\u0e15\u0e4c\u0e40\u0e04\u0e25\u0e37\u0e48\u0e2d\u0e19\u0e17\u0e35\u0e48<\/a><\/h3><\/div><\/div><\/div><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>
<\/div><\/section>","protected":false},"excerpt":{"rendered":"","protected":false},"author":1,"featured_media":6625,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_seopress_titles_title":"","_seopress_titles_desc":"","_seopress_robots_index":"","_seopress_robots_follow":"","_seopress_robots_imageindex":"","_seopress_robots_snippet":"","_seopress_robots_primary_cat":"","_seopress_robots_breadcrumbs":"","_seopress_robots_freeze_modified_date":"","_seopress_robots_custom_modified_date":"","_seopress_robots_canonical":"","_seopress_social_fb_title":"","_seopress_social_fb_desc":"","_seopress_social_fb_img":"","_seopress_social_fb_img_attachment_id":0,"_seopress_social_fb_img_width":0,"_seopress_social_fb_img_height":0,"_seopress_social_twitter_title":"","_seopress_social_twitter_desc":"","_seopress_social_twitter_img":"","_seopress_social_twitter_img_attachment_id":0,"_seopress_social_twitter_img_width":0,"_seopress_social_twitter_img_height":0,"_seopress_redirections_value":"","_seopress_redirections_enabled":"","_seopress_redirections_enabled_regex":"","_seopress_redirections_logged_status":"","_seopress_redirections_param":"","_seopress_redirections_type":0,"_seopress_analysis_target_kw":"","themepark_post_bcolor":"#f5f5f5","themepark_post_width":"100% dong","themepark_post_img":"","themepark_post_img_po":"left","themepark_post_img_re":false,"themepark_post_img_cover":false,"themepark_post_img_fixed":false,"themepark_post_hide_title":true,"themepark_post_main_b":"","themepark_post_main_p":100,"themepark_paddingblock":true,"_geo_short_summary":"SIASUN's Mobile Robot Statistical Analysis System leverages the IMRS data lake for multi-dimensional data acquisition and visual analytics, enabling real-time fleet monitoring and data-driven optimization.","_geo_structured_desc":"The Mobile Robot Statistical Analysis System is a comprehensive data analytics platform built on the IMRS data lake. It provides multi-dimensional data acquisition and visual analytics for mobile robot fleets, consolidating real-time robot status, task execution, and equipment health data. Insights are presented through dashboards and customized reports. The system supports intelligent decision-making for route optimization, dispatching strategies, and production takt improvement. It also enables predictive maintenance to reduce unplanned downtime risks. Key advantages include unified data capture and visualization of status, tasks, and health; multi-dimensional reports covering process, equipment, tasks, and energy metrics; decision support analytics for optimizing routes, dispatching, and takt time; and predictive maintenance to forecast health trends and reduce downtime. Case studies demonstrate its application in global new energy giants and century-old automobile brands, as well as the lithium industry.","_geo_faqs":"[{\"question\":\"What is the SIASUN Mobile Robot Statistical Analysis System?\",\"answer\":\"It is a data analytics platform built on the IMRS data lake that provides multi-dimensional data acquisition and visual analytics for mobile robot fleets, enabling real-time monitoring and data-driven optimization.\"},{\"question\":\"What data does the system capture and analyze?\",\"answer\":\"The system captures and analyzes real-time robot status, task execution, and equipment health data, consolidating them for visual presentation and reporting.\"},{\"question\":\"How does the system support decision-making?\",\"answer\":\"It supports intelligent decision-making by providing analytics for route optimization, dispatching strategies, and production takt improvement, as well as predictive maintenance to forecast health trends and reduce downtime.\"},{\"question\":\"What industries have implemented this system?\",\"answer\":\"The system has been implemented in global new energy giants, century-old automobile brands, and the lithium industry.\"}]","_geo_key_points":"[\"Built on the IMRS data lake for multi-dimensional data acquisition and visual analytics\",\"Consolidates real-time robot status, task execution, and equipment health data\",\"Presents insights through dashboards and customized reports\",\"Supports intelligent decision-making for route optimization, dispatching, and takt improvement\",\"Enables predictive maintenance to reduce unplanned downtime risks\",\"Provides multi-dimensional reports on process, equipment, tasks, and energy metrics\"]","_geo_target_audience":"Operations managers, logistics engineers, and automation specialists at manufacturing and warehousing facilities seeking to optimize mobile robot fleet performance through data-driven analytics and real-time monitoring.","_geo_content_type":"","_geo_last_modified":"2026-07-03T08:36:21+08:00","_geo_version":1,"themepark_seo_title":"SIASUN Mobile Robot Statistical Analysis System | Data-Driven Fleet Optimization","themepark_seo_description":"SIASUN\u2019s Mobile Robot Statistical Analysis System delivers powerful analytics for AGV\/AMR fleets. Monitor performance, analyze trends, and maximize operational efficiency with real-time data insights. Request a demo.","footnotes":""},"categories":[50],"tags":[],"class_list":["post-6615","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-imrs-2-0-software-platform"],"metadata":{"footnotes":[""],"themepark_post_width":["100% dong"],"themepark_post_img":[""],"themepark_post_img_re":[""],"themepark_post_img_cover":[""],"themepark_post_img_fixed":[""],"themepark_post_hide_title":["1"],"themepark_paddingblock":["1"],"catce":["sidebar-widgets4"],"views":["3371"],"_wp_old_slug":["sp160-160-3-05-new","fork-type-handling-mobile-robot"],"_canshu":["a:6:{i:0;a:5:{s:5:\"title\";s:15:\"Load capacity: \";s:4:\"text\";s:7:\"1000 kg\";s:2:\"f1\";i:18;s:2:\"f2\";s:0:\"\";s:2:\"f3\";s:0:\"\";}i:1;a:5:{s:5:\"title\";s:20:\"Navigation accuracy:\";s:4:\"text\";s:16:\" \u00b110 mm \/ \u00b11\u00b0\";s:2:\"f1\";i:18;s:2:\"f2\";s:0:\"\";s:2:\"f3\";s:0:\"\";}i:2;a:5:{s:5:\"title\";s:14:\"Drive system: \";s:4:\"text\";s:27:\"Single-steering-wheel drive\";s:2:\"f1\";s:0:\"\";s:2:\"f2\";s:0:\"\";s:2:\"f3\";s:0:\"\";}i:3;a:5:{s:5:\"title\";s:15:\"Lifting stroke:\";s:4:\"text\";s:7:\"1000 mm\";s:2:\"f1\";s:0:\"\";s:2:\"f2\";s:0:\"\";s:2:\"f3\";s:0:\"\";}i:4;a:5:{s:5:\"title\";s:21:\"Lift platform float: \";s:4:\"text\";s:34:\"X \u00b1125 mm; Y \u00b150 mm; Angle \u00b12\u00b0\";s:2:\"f1\";i:18;s:2:\"f2\";s:0:\"\";s:2:\"f3\";s:0:\"\";}i:5;a:5:{s:5:\"title\";s:19:\"Lifting mechanism: \";s:4:\"text\";s:50:\"Single-lift scissor structure, servo motor lifting\";s:2:\"f1\";i:18;s:2:\"f2\";s:0:\"\";s:2:\"f3\";s:0:\"\";}}"],"_thumbnail_id":["6625"],"_wp_old_date":["2024-05-28","2024-05-29","2026-02-03","2026-01-20"],"ao_post_optimize":["a:6:{s:16:\"ao_post_optimize\";s:2:\"on\";s:19:\"ao_post_js_optimize\";s:2:\"on\";s:20:\"ao_post_css_optimize\";s:2:\"on\";s:12:\"ao_post_ccss\";s:2:\"on\";s:16:\"ao_post_lazyload\";s:2:\"on\";s:15:\"ao_post_preload\";s:0:\"\";}"],"_dp_original":["6612"],"_edit_last":["1"],"_edit_lock":["1772589194:1"],"themepark_seo_title":["SIASUN Mobile Robot Statistical Analysis System | Data-Driven Fleet Optimization"],"themepark_seo_description":["SIASUN\u2019s Mobile Robot Statistical Analysis System delivers powerful analytics for AGV\/AMR fleets. Monitor performance, analyze trends, and maximize operational efficiency with real-time data insights. Request a demo."],"themepark_seo_keyword":["Mobile Robot Statistical Analysis System, AGV Data Analytics Platform, Mobile Robot Fleet Performance Monitoring, Siasun Robotics Analytics, AGV Operational Data Analysis, Robot Fleet Efficiency Metrics, Material Handling Data Visualization, Real-Time Robot Fleet Tracking, OEE Optimization for Robotics, Logistics Performance Dashboard, Automated Vehicle Data Aggregation, AMR Utilization Statistics, Factory Automation Data Reporting, Predictive Maintenance for Mobile Robots, Multi-Robot System Analytics, Warehouse Data Intelligence, Manufacturing Analytics Software, Robot Traffic Pattern Analysis, MES Data Integration Tools, WMS Performance Reporting, Industrial IoT Robot Data, Fleet Management Business Intelligence"],"_trp_automatically_translated_slug_es_ES":["sistema-de-analisis-estadistico-de-robots-moviles"],"_trp_automatically_translated_slug_ja":["\u30e2\u30d0\u30a4\u30eb\u30ed\u30dc\u30c3\u30c8\u7d71\u8a08\u89e3\u6790\u30b7\u30b9\u30c6\u30e0"],"_trp_automatically_translated_slug_de_DE":["statistisches-analysesystem-fur-mobile-roboter"],"_trp_automatically_translated_slug_th":["\u0e23\u0e30\u0e1a\u0e1a\u0e27\u0e34\u0e40\u0e04\u0e23\u0e32\u0e30\u0e2b\u0e4c\u0e17\u0e32\u0e07\u0e2a\u0e16\u0e34\u0e15\u0e34\u0e2a"],"_geo_short_summary":["SIASUN's Mobile Robot Statistical Analysis System leverages the IMRS data lake for multi-dimensional data acquisition and visual analytics, enabling real-time fleet monitoring and data-driven optimization."],"_geo_structured_desc":["The Mobile Robot Statistical Analysis System is a comprehensive data analytics platform built on the IMRS data lake. It provides multi-dimensional data acquisition and visual analytics for mobile robot fleets, consolidating real-time robot status, task execution, and equipment health data. Insights are presented through dashboards and customized reports. The system supports intelligent decision-making for route optimization, dispatching strategies, and production takt improvement. It also enables predictive maintenance to reduce unplanned downtime risks. Key advantages include unified data capture and visualization of status, tasks, and health; multi-dimensional reports covering process, equipment, tasks, and energy metrics; decision support analytics for optimizing routes, dispatching, and takt time; and predictive maintenance to forecast health trends and reduce downtime. Case studies demonstrate its application in global new energy giants and century-old automobile brands, as well as the lithium industry."],"_geo_faqs":["[{\"question\":\"What is the SIASUN Mobile Robot Statistical Analysis System?\",\"answer\":\"It is a data analytics platform built on the IMRS data lake that provides multi-dimensional data acquisition and visual analytics for mobile robot fleets, enabling real-time monitoring and data-driven optimization.\"},{\"question\":\"What data does the system capture and analyze?\",\"answer\":\"The system captures and analyzes real-time robot status, task execution, and equipment health data, consolidating them for visual presentation and reporting.\"},{\"question\":\"How does the system support decision-making?\",\"answer\":\"It supports intelligent decision-making by providing analytics for route optimization, dispatching strategies, and production takt improvement, as well as predictive maintenance to forecast health trends and reduce downtime.\"},{\"question\":\"What industries have implemented this system?\",\"answer\":\"The system has been implemented in global new energy giants, century-old automobile brands, and the lithium industry.\"}]"],"_geo_key_points":["[\"Built on the IMRS data lake for multi-dimensional data acquisition and visual analytics\",\"Consolidates real-time robot status, task execution, and equipment health data\",\"Presents insights through dashboards and customized reports\",\"Supports intelligent decision-making for route optimization, dispatching, and takt improvement\",\"Enables predictive maintenance to reduce unplanned downtime risks\",\"Provides multi-dimensional reports on process, equipment, tasks, and energy metrics\"]"],"_geo_target_audience":["Operations managers, logistics engineers, and automation specialists at manufacturing and warehousing facilities seeking to optimize mobile robot fleet performance through data-driven analytics and real-time monitoring."],"_geo_manual_overrides":["[\"_geo_short_summary\",\"_geo_structured_desc\",\"_geo_faqs\",\"_geo_key_points\",\"_geo_target_audience\"]"],"_geo_last_modified":["2026-07-03T08:36:21+08:00"],"_geo_version":["1"],"_geo_has_data":["1"]},"medium_url":"https:\/\/en.siasun.com\/wp-content\/uploads\/2026\/02\/20260205-133205.jpg","thumbnail_url":"https:\/\/en.siasun.com\/wp-content\/uploads\/2026\/02\/20260205-133205-150x150.jpg","full_url":"https:\/\/en.siasun.com\/wp-content\/uploads\/2026\/02\/20260205-133205.jpg","_links":{"self":[{"href":"https:\/\/en.siasun.com\/th\/wp-json\/wp\/v2\/posts\/6615","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/en.siasun.com\/th\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/en.siasun.com\/th\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/en.siasun.com\/th\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/en.siasun.com\/th\/wp-json\/wp\/v2\/comments?post=6615"}],"version-history":[{"count":3,"href":"https:\/\/en.siasun.com\/th\/wp-json\/wp\/v2\/posts\/6615\/revisions"}],"predecessor-version":[{"id":6635,"href":"https:\/\/en.siasun.com\/th\/wp-json\/wp\/v2\/posts\/6615\/revisions\/6635"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/en.siasun.com\/th\/wp-json\/wp\/v2\/media\/6625"}],"wp:attachment":[{"href":"https:\/\/en.siasun.com\/th\/wp-json\/wp\/v2\/media?parent=6615"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/en.siasun.com\/th\/wp-json\/wp\/v2\/categories?post=6615"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/en.siasun.com\/th\/wp-json\/wp\/v2\/tags?post=6615"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}