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紧固件数字库-GB5781-2016螺栓编码管理数据

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浙江省数据知识产权登记平台2024-11-13 更新2024-11-14 收录
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本数据有助于紧固件GB5781-2016螺栓产品属性管理及产品唯一简化编码生成和管理,实现产品的唯一性匹配。十二角螺钉产品属性繁多有如:产品类目、产品标准名称、产品标准代号、产品规格(由直径、长度、牙距、牙型组成)、材质、强度、材料、表面处理等12个属性构成,本数据通过将产品12个属性名称和属性值进行统一规范的管理,产品描述的所有属性值多的长达50个文字以上,很难在后续的ERP、WMS、MES等系统中调用和描述,并且无法进行产品唯一性的匹配和管理,为此将产品的12个属性值通过类似于Base64 的自定义编码(仅包含字母和数字一共33个)的方式转换成12~19位长的产品唯一编码实现产品的唯一性匹配和检索,并且通过产品的唯一性编码生成一个对于的产品二维码,快速的进行扫码识别进行后续系统平台的调用。1、数据采集: 通过发行的紧固件标准手册、螺纹公差、机械性能、材质手册等,获得紧固件GB5781-2016螺栓产品的属性数据和参数,从本单位开发运营的“工业零部件数字库-【紧固件】标准底层系统”上采集紧固件产品的属性数据,包括:标准名称、标准代号、产品规格(细化为直径、长度、牙距、牙型等四项)、材质、强度、材料、材料化学成分、材料机械性能、表面处理等并生成属性对应的ID代号。 2、算法加工方法: 第一步:从工业零部件数字库-紧固件中获取产品数据,包括品类、标准【标准名称和标准代号】、规格(由直径、长度、牙距、牙型组成)以及材质、强度、材料、表色等数据及属性对应的ID代号。 第二步:将获取的品类、标准、规格3个属性的的ID号,使用33位自定义编码(仅含字母和数字:H1VGSCNXQTF6L7MR2UB04ZP89JE5Y3DKWA)转换成特定的短编码。 第三步:将获取的材质、强度、材料、表色属性值字符串通过哈希算法得到哈希值,再将哈希值使用33位自定义编码转换成特定的短编码。 第四部:将步骤二、三转换后获得的,品类、标准、规格及其他属性的自定义短码通过横杠连接在一起形成产品的唯一编码。

This dataset facilitates the attribute management, generation and management of unique simplified codes for GB5781-2016 bolt fastener products, enabling unique product matching. Twelve-point screw products have numerous attributes, totaling 12 attributes including product category, product standard name, product standard code, product specification (composed of diameter, length, pitch and thread profile), material quality, strength, raw material and surface treatment. This dataset implements unified standardized management of the 12 attribute names and their corresponding values. However, some attribute values in product descriptions can exceed 50 characters in length, making it difficult to invoke and describe in subsequent systems such as ERP, WMS and MES, and preventing unique product matching and management. To solve this problem, the 12 attribute values of the products are converted into 12-to-19-bit unique product codes via a custom encoding scheme similar to Base64 (using only 33 alphanumeric characters), to realize unique product matching and retrieval. Additionally, a corresponding product QR code is generated based on the unique product code, enabling fast scanning and recognition for invocation via subsequent system platforms. 1. Data Collection: Attribute data and parameters of GB5781-2016 bolt fastener products are obtained from published fastener standard manuals, thread tolerance specifications, mechanical property manuals and material manuals. Attribute data of fastener products are also collected from the "Industrial Component Digital Library - [Fasteners] Standard Backend System" developed and operated by our organization, including standard name, standard code, product specification (refined into four items: diameter, length, pitch and thread profile), material quality, strength, raw material, material chemical composition, material mechanical properties, surface treatment and other items, with corresponding ID codes generated for each attribute. 2. Algorithm Processing Method Step 1: Retrieve product data from the Industrial Component Digital Library - Fasteners, including category, standard [standard name and standard code], specification (composed of diameter, length, pitch and thread profile), material quality, strength, raw material, surface treatment and other data, as well as the corresponding ID codes for each attribute. Step 2: Convert the ID numbers of the three attributes (category, standard and specification) into specific short codes using the 33-character custom encoding (only alphanumeric: H1VGSCNXQTF6L7MR2UB04ZP89JE5Y3DKWA). Step 3: Convert the attribute value strings of material quality, strength, raw material and surface treatment into hash values via a hashing algorithm, then convert the hash values into specific short codes using the 33-character custom encoding. Step 4: Concatenate the custom short codes of category, standard, specification and other attributes obtained from Step 2 and Step 3 with hyphens to form the unique product code.
提供机构:
杭州优工品科技有限公司
创建时间:
2024-10-25
搜集汇总
数据集介绍
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特点
该数据集为紧固件GB5781-2016螺栓的编码管理数据,包含1002条记录,每周更新。通过自定义编码和哈希算法生成产品唯一编码,便于产品属性管理和唯一性匹配,适用于ERP、WMS、MES等系统。
以上内容由遇见数据集搜集并总结生成
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