{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T07:18:51Z","timestamp":1775200731783,"version":"3.50.1"},"reference-count":38,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2022,12,4]],"date-time":"2022-12-04T00:00:00Z","timestamp":1670112000000},"content-version":"am","delay-in-days":337,"URL":"http:\/\/www.elsevier.com\/open-access\/userlicense\/1.0\/"}],"funder":[{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia","doi-asserted-by":"publisher","award":["UIDB\/50022\/2020"],"award-info":[{"award-number":["UIDB\/50022\/2020"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Journal of Manufacturing Systems"],"published-print":{"date-parts":[[2022,1]]},"DOI":"10.1016\/j.jmsy.2021.11.014","type":"journal-article","created":{"date-parts":[[2021,12,4]],"date-time":"2021-12-04T10:55:46Z","timestamp":1638615346000},"page":"270-285","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":21,"special_numbering":"C","title":["Assessing the impact of automation in pharmaceutical quality control labs using a digital twin"],"prefix":"10.1016","volume":"62","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8927-6577","authenticated-orcid":false,"given":"Tiago","family":"Coito","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6285-8737","authenticated-orcid":false,"given":"Miguel S.E.","family":"Martins","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9562-1808","authenticated-orcid":false,"given":"Bernardo","family":"Firme","sequence":"additional","affiliation":[]},{"given":"Jo\u00e3o","family":"Figueiredo","sequence":"additional","affiliation":[]},{"given":"Susana M.","family":"Vieira","sequence":"additional","affiliation":[]},{"given":"Jo\u00e3o M.C.","family":"Sousa","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.jmsy.2021.11.014_bib0005","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1038\/nrd3681","article-title":"Diagnosing the decline in pharmaceutical R&D efficiency","volume":"11","author":"Scannell","year":"2012","journal-title":"Nat Rev Drug Discov"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0010","series-title":"Problems facing the pharmaceutical industry and approaches to ensure long term viability","author":"Baines","year":"2010"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0015","doi-asserted-by":"crossref","first-page":"929","DOI":"10.1016\/j.compchemeng.2003.09.022","article-title":"Pharmaceutical supply chains: key issues and strategies for optimisation","volume":"28","author":"Shah","year":"2004","journal-title":"Comput Chem Eng"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0020","doi-asserted-by":"crossref","first-page":"9014","DOI":"10.1016\/j.ifacol.2017.08.1582","article-title":"Simulation model of a quality control laboratory in pharmaceutical industry","volume":"50","author":"Costigliola","year":"2017","journal-title":"IFAC-PapersOnLine"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0025","doi-asserted-by":"crossref","first-page":"1910","DOI":"10.1134\/S0005117912110124","article-title":"Laboratory analysis planning system for industrial enterprises","volume":"73","author":"Dudnikov","year":"2012","journal-title":"Autom Remote Control"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0030","volume":"Vol. 2","author":"World Health Organization","year":"2007"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0035","first-page":"481","article-title":"Industry 4.0 smart reconfigurable manufacturing machines","volume":"59","author":"Morgan","year":"2021","journal-title":"Int J Ind Manuf Syst Eng"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0040","first-page":"68","article-title":"Resource scheduling in QC laboratories","volume":"32","author":"Maslaton","year":"2012","journal-title":"Pharm Eng"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0045","series-title":"Scheduling: theory, algorithms, and systems","author":"Pinedo","year":"2016"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0050","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.trac.2016.12.011","article-title":"Trends in Analytical Chemistry the dawn of unmanned analytical laboratories","volume":"88","author":"Prabhu","year":"2017","journal-title":"Trends Analyt Chem"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0055","first-page":"346","article-title":"Review of digital twin about concepts, technologies, and industrial applications","volume":"58","author":"Liu","year":"2020","journal-title":"Int J Ind Manuf Syst Eng"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0060","first-page":"3","article-title":"Enabling technologies and tools for digital twin","volume":"58","author":"Qi","year":"2021","journal-title":"Int J Ind Manuf Syst Eng"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0065","first-page":"36","article-title":"How to model and implement connections between physical and virtual models for digital twin application","volume":"58","author":"Jiang","year":"2021","journal-title":"Int J Ind Manuf Syst Eng"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0070","first-page":"1","article-title":"Industrial informatics design, use and innovation: perspectives and services","author":"Holmstr\u00f6m","year":"2010","journal-title":"Ind Informatics Des Use Innov Perspect Serv"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0075","series-title":"McGraw-Hill series in industrial engineering and management science","article-title":"Simulation modeling and analysis","author":"Law","year":"2015"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0080","first-page":"119","article-title":"Digital twins-based smart manufacturing system design in Industry 4.0: A review","volume":"60","author":"Leng","year":"2021","journal-title":"Int J Ind Manuf Syst Eng"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0085","doi-asserted-by":"crossref","first-page":"62","DOI":"10.3390\/automation2020004","article-title":"Intelligent sensors for real-time decision-making","volume":"2","author":"Coito","year":"2021","journal-title":"Automation"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0090","first-page":"146","article-title":"Digital twin enhanced dynamic job-shop scheduling","volume":"58","author":"Zhang","year":"2021","journal-title":"Int J Ind Manuf Syst Eng"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0095","first-page":"210","article-title":"A digital twin to train deep reinforcement learning agent for smart manufacturing plants: environment, interfaces and intelligence","volume":"58","author":"Xia","year":"2021","journal-title":"Int J Ind Manuf Syst Eng"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0100","first-page":"176","article-title":"A digital-twin visualized architecture for flexible manufacturing system","volume":"60","author":"Fan","year":"2021","journal-title":"Int J Ind Manuf Syst Eng"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0105","first-page":"231","article-title":"Modeling and implementation of a digital twin of material flows based on physics simulation","volume":"58","author":"Glatt","year":"2021","journal-title":"Int J Ind Manuf Syst Eng"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0110","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/S0003-2670(00)84294-4","article-title":"Enhancement of the performance of analytical laboratories by a digital simulation approach","volume":"159","author":"TAHM","year":"1984","journal-title":"Anal Chim Acta"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0115","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1002\/cem.1180020107","article-title":"Expert system for knowledge-based modelling of analytical laboratories as a tool for laboratory management","volume":"2","author":"Klaessens","year":"1988","journal-title":"J Chemom"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0120","doi-asserted-by":"crossref","first-page":"382","DOI":"10.1016\/j.jala.2004.10.001","article-title":"Concepts for dynamic scheduling in the laboratory","volume":"9","author":"Sch\u00e4fer","year":"2004","journal-title":"J Lab Autom"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0125","series-title":"Introduction to discrete event systems","author":"Cassandras","year":"2008"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0130","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1057\/978-1-349-95257-1_9","article-title":"Comparing discrete-event simulation and system dynamics: users\u2019 perceptions","author":"Tako","year":"2018","journal-title":"Syst Dyn"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0135","first-page":"1","article-title":"Pharmaceutical quality control laboratory digital twin\u2013A novel governance model for resource planning and scheduling","author":"Lopes","year":"2019","journal-title":"Int J Prod Res"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0140","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1016\/j.promfg.2020.02.017","article-title":"An RFID application for the process mapping automation","volume":"42","author":"Urso","year":"2020","journal-title":"Procedia Manuf"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0145","series-title":"Business process model and notation (BPMN) version 2.0","author":"OMG","year":"2011"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0150","doi-asserted-by":"crossref","DOI":"10.1016\/j.compind.2020.103329","article-title":"A middleware platform for intelligent automation: an industrial prototype implementation","volume":"123","author":"Coito","year":"2020","journal-title":"Comput Ind"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0155","first-page":"368","article-title":"Modern analytical chemistry","author":"Harvey","year":"2000","journal-title":"McGraw-Hill High Educ"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0160","doi-asserted-by":"crossref","first-page":"691","DOI":"10.1080\/00207543.2010.543173","article-title":"Scheduling with multiple tasks per job - the case of quality control laboratories in the pharmaceutical industry","volume":"50","author":"Ruiz-Torres","year":"2012","journal-title":"Int J Prod Res"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0165","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.chemolab.2012.07.001","article-title":"Trends in laboratory information management system","volume":"118","author":"Prasad","year":"2012","journal-title":"Chemometr Intell Lab Syst"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0170","series-title":"Simio and simulation: modeling, analysis; applications. 5th edit","author":"Smith","year":"2018"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0175","first-page":"2","article-title":"Artificial intelligence and simulation in business","author":"Mahdavi","year":"2019","journal-title":"Anylogic"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0180","doi-asserted-by":"crossref","first-page":"474","DOI":"10.1016\/j.cie.2018.07.046","article-title":"An introductory guide for hybrid simulation modelers on the primary simulation methods in industrial engineering identified through a systematic review of the literature","volume":"124","author":"Galv\u00e3o Scheidegger","year":"2018","journal-title":"Comput Ind Eng"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0185","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1504\/IJISM.2021.113563","article-title":"The impact of intelligent automation in internal supply chains","volume":"1","author":"Coito","year":"2021","journal-title":"Int J Integr Supply Manag"},{"key":"10.1016\/j.jmsy.2021.11.014_bib0190","first-page":"530","article-title":"Industry 4.0 and Industry 5.0\u2014inception, conception and perception","volume":"61","author":"Xu","year":"2021","journal-title":"Int J Ind Manuf Syst Eng"}],"container-title":["Journal of Manufacturing Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0278612521002442?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0278612521002442?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,10,3]],"date-time":"2025-10-03T20:21:59Z","timestamp":1759522919000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0278612521002442"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1]]},"references-count":38,"alternative-id":["S0278612521002442"],"URL":"https:\/\/doi.org\/10.1016\/j.jmsy.2021.11.014","relation":{},"ISSN":["0278-6125"],"issn-type":[{"value":"0278-6125","type":"print"}],"subject":[],"published":{"date-parts":[[2022,1]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Assessing the impact of automation in pharmaceutical quality control labs using a digital twin","name":"articletitle","label":"Article Title"},{"value":"Journal of Manufacturing Systems","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.jmsy.2021.11.014","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2021 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.","name":"copyright","label":"Copyright"}]}}