MediaWiki API result

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        "gapcontinue": "Real_asset",
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    "warnings": {
        "main": {
            "*": "Subscribe to the mediawiki-api-announce mailing list at <https://lists.wikimedia.org/postorius/lists/mediawiki-api-announce.lists.wikimedia.org/> for notice of API deprecations and breaking changes."
        },
        "revisions": {
            "*": "Because \"rvslots\" was not specified, a legacy format has been used for the output. This format is deprecated, and in the future the new format will always be used."
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    "query": {
        "pages": {
            "854": {
                "pageid": 854,
                "ns": 0,
                "title": "Readiness of production facilities",
                "revisions": [
                    {
                        "contentformat": "text/x-wiki",
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                        "*": "'''Readiness of [[production]] facilities''' refers to the ability of a facility to quickly and efficiently produce goods or services. Factors that determine the readiness of production facilities include:\n* Equipment and machinery: The condition, age, and capacity of the equipment and machinery used in the production [[process]] can affect the readiness of the facility.\n* Maintenance and repair: The maintenance schedule and effectiveness of maintenance and repair can affect the readiness of the facility.\n* Labor: The number and skill level of the workers involved in the [[production process]] can affect the readiness of the facility.\n* Materials and supplies: The availability and [[quality]] of the materials and supplies used in the production process can affect the readiness of the facility.\n* Production process: The [[efficiency]] and effectiveness of the production process, including the design of the [[production line]], can affect the readiness of the facility.\n* [[Market]] [[demand]]: The level of [[market demand]] for the goods or services being produced can affect the readiness of the facility.\n* [[Government]] regulations: Compliance with government regulations such as safety, [[environment]], [[labor laws]], and taxes can affect the readiness of the facility.\n* [[Information]] [[technology]]: The use of technology such as automation, computer systems, and software can affect the readiness of the facility.\n* [[Logistics]]: The availability and efficiency of the logistics infrastructure such as transportation, warehouses, and inventory management can affect the readiness of the facility.\n* Finances: The availability and stability of the [[financial resources]] can affect the readiness of the facility\n\nOverall, the readiness of production facilities depends on the proper functioning of equipment, machinery, and the production process, as well as the [[availability of resources]], compliance with regulations, market demand and the efficiency of logistics and IT systems.\n\n==Calculation of readiness==\nThere are several ways to calculate the readiness of production facilities, depending on the specific [[goals and objectives]] of the [[organization]]. One common [[method]] is to use a facility readiness index, which is a numerical value that represents the overall readiness of the facility. This index can be calculated using the following steps:\n* Identify the critical factors that affect the readiness of the facility. These may include equipment and machinery, maintenance and repair, labor, materials and supplies, production process, market demand, government regulations, and logistics.\n* Assign a weighting factor to each critical factor. This weighting factor represents the importance of each factor in relation to the overall readiness of the facility.\n* Assess the current performance of the facility for each critical factor. This can be done through inspections, audits, or other forms of [[evaluation]].\n* Multiply the weighting factor for each critical factor by its corresponding performance score to obtain a weighted score for each critical factor.\n* Sum the weighted scores for all critical factors to obtain the facility readiness index.\n\nFor example, if equipment and machinery is assigned a weighting factor of 0.3, and its current performance is rated as 80%, the weighted score for equipment and machinery would be 0.3 x 80 = 24. Similarly, if labor is assigned a weighting factor of 0.2, and its current performance is rated as 90%, the weighted score for labor would be 0.2 x 90 = 18. If we sum all the weighted scores, the facility readiness index would be 24+18+...+x (x represents the last weighted score)\n\nAnother way to calculate readiness of production facilities is through the use of [[performance indicators]] such as production yield, efficiency, capacity utilization, and OEE (Overall Equipment Effectiveness)\n\nIt is important to note that the readiness of production facilities should be regularly assessed and updated to ensure that the facility is operating at its full potential.\n\n{{infobox5|list1={{i5link|a=[[Production capacity]]}} &mdash; {{i5link|a=[[Production reserve]]}} &mdash; {{i5link|a=[[Capacity analysis]]}} &mdash; {{i5link|a=[[Direct material]]}} &mdash; {{i5link|a=[[Factor of production]]}} &mdash; {{i5link|a=[[Uniformity of production]]}} &mdash; {{i5link|a=[[Workplace]]}} &mdash; {{i5link|a=[[Cost of processing]]}} &mdash; {{i5link|a=[[Storage and handling infrastructure]]}} }}\n\n==References==\n* Ahuja, I. P. S. (2009). ''[http://link.springer.com/10.1007/978-1-84882-472-0_17 Total productive maintenance]''. In Handbook of Maintenance [[Management]] and Engineering (p. 417-459). Springer London.\n[[Category:Production management]]\n[[pl:Gotowo\u015b\u0107 urz\u0105dze\u0144 produkcyjnych]]"
                    }
                ]
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            "4860": {
                "pageid": 4860,
                "ns": 0,
                "title": "Real-time data collection and analysis",
                "revisions": [
                    {
                        "contentformat": "text/x-wiki",
                        "contentmodel": "wikitext",
                        "*": "'''Real-time data collection and analysis''' refers to the [[process]] of gathering data and analyzing it in real-time, or near real-time. This means that the data is collected and analyzed as it is generated, rather than being stored and analyzed later.\n\nThere are several benefits to real-time data collection and analysis, including:\n* '''Faster decision-making''': With real-time data, organizations can make decisions based on the most up-to-date [[information]], rather than relying on outdated data.\n* '''Improved [[efficiency]]''': Real-time data can be used to optimize operations and improve efficiency by identifying and addressing problems as they occur.\n* '''Better [[customer]] [[service]]''': Real-time data can be used to improve customer service by identifying and addressing customer [[needs]] and concerns in a timely manner.\n* '''Better [[risk]] [[management]]''': Real-time data can be used to identify and mitigate potential risks, such as detecting and preventing fraud.\n* '''[[Cost]] savings''': Real-time data can be used to identify and address inefficiencies and reduce costs.\n* '''Predictive analytics''': Real-time data can be used to predict future outcomes and make proactive decisions.\n\nReal-time data collection and analysis typically involves the use of technologies such as sensors, IoT devices, and [[cloud computing]] platforms. These technologies can be used to collect and transmit data in real-time, and then analyze it using advanced analytical tools such as machine learning algorithms and statistical models.\n\nOverall, Real-time data collection and analysis allows organizations to gain a more complete and accurate understanding of their operations, customers, and markets, which in turn enables them to make better decisions, improve performance and increase efficiency.\n\n{{infobox5|list1={{i5link|a=[[Harvesting strategy]]}} &mdash; {{i5link|a=[[Information processing]]}} &mdash; {{i5link|a=[[Ai in accounting]]}} &mdash; {{i5link|a=[[Computer information systems]]}} &mdash; {{i5link|a=[[Processing of information]]}} &mdash; {{i5link|a=[[Ai in manufacturing]]}} &mdash; {{i5link|a=[[Analysis and interpretation]]}} &mdash; {{i5link|a=[[Data and information]]}} &mdash; {{i5link|a=[[Telematics and informatics]]}} }}\n\n==References==\n* Kim, H. C. (2019). ''[https://www.koreascience.or.kr/article/JAKO201914260902411.pdf A Study on The Real-Time Data Collection/Analysis/Processing Intelligent IoT]''. The Journal of the Korea institute of electronic [[communication]] sciences, 14(2), 317-322.\n[[Category:Quality 4.0]]"
                    }
                ]
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