1
|
Andrews DJ, Eddy TL, Hollenback KS, Sreekumar S, Loose DC, Pennetti CA, Polmateer TL, Haug JC, Oliver-Clark LI, Williams JY, Manasco MC, Smith S, Lambert JH. Enterprise risk management for automation in correctional facilities with pandemic and other stressors. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2023; 43:820-837. [PMID: 36114602 DOI: 10.1111/risa.14004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Real-time tracking of tool and equipment inventories is a critical function of many organizations and sectors. For prisons and correctional facilities, tracking and monitoring of assets such as cookware, hardware, keys, janitorial equipment, vocational/technical specialty tools, etc., is essential for safety, security, trust, efficiency, education, etc. The performance of automated systems for this purpose can be diminished by a variety of emergent and future sociotechnical factors alone and in combination. This article introduces a methodology for contractor evaluation and selection in acquisition of innovative asset management systems, with an emphasis on evolving system requirements under uncertainty. The methodology features a scenario-based preferences analysis of emergent and future conditions that are disruptive to the performance of the asset-control system. The conditions are across technologies, operating environments, regulations, workforce behaviors, offender behaviors, prices and markets, organizations, cyber threats, etc. The methodology addresses the influence and interaction of the conditions to disrupt system priorities. Examples include: (i) infectious disease disrupting priorities among requirements and (ii) radio-frequency identification (RFID) and wireless-technology innovations disrupting priorities among stakeholders. The combinations of conditions that most and least matter for the system acquisition are characterized. The methodology constitutes a risk register for monitoring sources of risk to project performance, schedule, and cost throughout the system lifecycle. The results will be of interest to both practitioners and scholars engaged in systems acquisition as the pandemic interacts with other factors to affect risk, uncertainty, and resilience of organizational missions and operations.
Collapse
Affiliation(s)
- Daniel J Andrews
- School of Engineering Systems and Environment, University of Virginia, Charlottesville, Virginia, USA
| | - Timothy L Eddy
- School of Engineering Systems and Environment, University of Virginia, Charlottesville, Virginia, USA
| | - Kelsey S Hollenback
- School of Engineering Systems and Environment, University of Virginia, Charlottesville, Virginia, USA
| | - Shravan Sreekumar
- School of Engineering Systems and Environment, University of Virginia, Charlottesville, Virginia, USA
| | - Davis C Loose
- School of Engineering Systems and Environment, University of Virginia, Charlottesville, Virginia, USA
| | - Cody A Pennetti
- School of Engineering Systems and Environment, University of Virginia, Charlottesville, Virginia, USA
| | - Thomas L Polmateer
- School of Engineering Systems and Environment, University of Virginia, Charlottesville, Virginia, USA
| | | | - Lessie I Oliver-Clark
- Department of Applied Engineering Technology, Virginia State University, Petersburg, Virginia, USA
| | - Joi Y Williams
- Department of Applied Engineering Technology, Virginia State University, Petersburg, Virginia, USA
| | - Mark C Manasco
- Commonwealth Center for Advanced Logistics Systems, Richmond, Virginia, USA
| | - Steven Smith
- Virginia Department of Corrections, Richmond, Virginia, USA
| | - James H Lambert
- School of Engineering Systems and Environment, University of Virginia, Charlottesville, Virginia, USA
| |
Collapse
|
2
|
Gonzalez-Compean JL, Sosa-Sosa VJ, Garcia-Hernandez JJ, Galeana-Zapien H, Reyes-Anastacio HG. A Blockchain and Fingerprinting Traceability Method for Digital Product Lifecycle Management. SENSORS (BASEL, SWITZERLAND) 2022; 22:8400. [PMID: 36366095 PMCID: PMC9655076 DOI: 10.3390/s22218400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 10/28/2022] [Accepted: 10/28/2022] [Indexed: 06/16/2023]
Abstract
The rise of digitalization, sensory devices, cloud computing and internet of things (IoT) technologies enables the design of novel digital product lifecycle management (DPLM) applications for use cases such as manufacturing and delivery of digital products. The verification of the accomplishment/violations of agreements defined in digital contracts is a key task in digital business transactions. However, this verification represents a challenge when validating both the integrity of digital product content and the transactions performed during multiple stages of the DPLM. This paper presents a traceability method for DPLM based on the integration of online and offline verification mechanisms based on blockchain and fingerprinting, respectively. A blockchain lifecycle registration model is used for organizations to register the exchange of digital products in the cloud with partners and/or consumers throughout the DPLM stages as well as to verify the accomplishment of agreements at each DPLM stage. The fingerprinting scheme is used for offline verification of digital product integrity and to register the DPLM logs within digital products, which is useful in either dispute or violation of agreements scenarios. We built a DPLM service prototype based on this method, which was implemented as a cloud computing service. A case study based on the DPLM of audios was conducted to evaluate this prototype. The experimental evaluation revealed the ability of this method to be applied to DPLM in real scenarios in an efficient manner.
Collapse
|
3
|
Traceability Models and Traceability Systems to Accelerate the Transition to a Circular Economy: A Systematic Review. SUSTAINABILITY 2022. [DOI: 10.3390/su14095469] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Research and implementation efforts and investment in the circular economy are rising sharply. With the high stakes associated with achievements in the field, an increasing emphasis on evaluation, transparency and accountability are to be expected. All require high-quality data, methodologies and tools that are able to improve results and to assess and document the implementation processes and outcomes. A challenging key issue in the implementation of a circular economy is ensuring coordination, control and transparency within a network of parties. Traceability models and systems are vital pillars of such an endeavor, but a preliminary search of the available literature revealed a rather unstable and fragmented research field and practice. The objective of this systematic review was to examine those studies discussing traceability models and traceability systems while connecting traceability capacities and outputs to implement the principles of the circular economy. The literature databases were searched on 6 January 2020, with an update for the entire year of 2020. Overall, 49 studies were included. By addressing eight specific research questions, we found that a link between traceability and the circular economy is yet to be established. Sound research and practice documentation are required to establish evidence regarding this connection, including methodologies that are able to support the design and implementation of business- and lifecycle-oriented, value-based traceability models and traceability systems, along with thorough evaluation methods and tools incorporating economic, social and environmental perspectives.
Collapse
|