HYBRID EVENT
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Harbin, China
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ICSQCIA · Registering as Listener
International Conference on Statistical Quality Control and Industrial Applications
27–28 Feb 2027
Harbin, China
Standard / Physical
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135
virtual · $175 in person
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1. Policy on Cancellations & Refunds :
A full refund is possible only if the cancellation request is submitted at least 70 days before the conference, with formal paperwork completed at least 60 days prior.
If cancellation occurs between 60 and 30 days before the event, partial refunds may be granted based on administrative costs incurred.
Cancellations made within 30 days of the event are non-refundable, though participants will receive a credit valid for one year.
Registrations made less than 30 days before the event are not eligible for refunds, but may be transferred to another ISIT conference.
Since this conference is hybrid format, the organizer reserves the right to conduct the event either in-person or virtually. Please note that no refunds will be issued due to changes in the event format.
Virtual registration fees are non-refundable. A credit will instead be issued for use at a future conference event.
2. Participation & Registration Requirements :
To attend an ISIT event, participants must complete the registration process within the stipulated time.
The event schedule, venue, and format are subject to changes at the discretion of the organizers, with prior notice sent via email.
ISIT is not liable for any financial losses resulting from changes in event details.
Fees paid for registration are strictly non-refundable.
If the primary author cannot participate, a co-author may attend instead, but refunds will not be granted for non-attendance.
3. Submission & Publication Norms :
Researchers submitting papers to ISIT must ensure their institution or supervisor is aware of their submission.
Each submission is subject to a rigorous peer review before being accepted for presentation.
Only papers linked to a completed registration will be included in conference proceedings.
The submitting author is considered the primary author; ISIT does not verify individual authorship claims.
If any concerns regarding authorship arise and are validated, the paper will be withdrawn without reconsideration.
Once a paper is removed, it cannot be reintroduced into any ISIT publication.
4. Travel & Accommodation Responsibilities :
Attendees are responsible for making their own travel and lodging arrangements.
ISIT does not provide logistical assistance for travel or accommodation.
The organization bears no responsibility for expenses incurred due to conference modifications or rescheduling.
5. Visa & Invitation Letter Policy :
Attendees are responsible for making their own travel and lodging arrangements.
ISIT does not provide logistical assistance for travel or accommodation.
The organization bears no responsibility for expenses incurred due to conference modifications or rescheduling.
ISIT does not engage directly with consulates or embassies on behalf of attendees.
Participants must handle their own visa applications and processes.
Important Information Regarding Invitation Letters:
The invitation letter is provided solely for conference attendance and does not serve as a document for immigration, employment, or residency purposes.
The letter assists in visa applications but does not guarantee visa approval.
ISIT holds no responsibility for visa denials or processing delays, and all related costs are borne by the applicant.
Any alterations or unauthorized use of the invitation letter will result in its invalidation and possible cancellation of conference participation.
Legal action may be pursued if the document is misused.
By accepting the invitation letter, attendees agree to comply with international travel regulations and ethical participation standards.
6. Registration Transfers :
Registrations may be transferred to another individual from the same institution if the original participant cannot attend.
Transfer requests must be made via email to
[email protected]
with necessary details and supporting documents.
Transfers must be requested at least 14 days before the event; otherwise, they will not be accommodated.
Transferred registrations are not eligible for refunds.
7. General Considerations :
Any modifications or cancellations must be communicated in writing to
[email protected]
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Registration confirms acknowledgment and acceptance of these policies.
ISIT does not initiate automatic transactions; all payments are voluntarily completed by registrants.
Once registered, participants must submit a conference registration form within three days for confirmation.
Travel plans should only be finalized after receiving the official conference itinerary, which will be shared 15 days before the event.
8. Conference Programme and Participation Policy :
Presentations from different but relevant academic areas may be combined by the Organiser within an interdisciplinary or multidisciplinary programme to encourage cross-disciplinary understanding, interaction, and future research partnerships.
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What you'll hear about
Session tracks covered across the event.
View all 11 tracks →
01
Advancements in Statistical Quality Control Techniques
This track focuses on the latest methodologies and innovations in statistical quality control. Researchers are encouraged to present their findings on new control charts and monitoring techniques that enhance quality assurance in various industries.
02
Applications of Six Sigma in Modern Manufacturing
This session explores the integration of Six Sigma methodologies in contemporary manufacturing processes. Papers should highlight case studies and empirical research demonstrating the impact of Six Sigma on quality improvement and operational efficiency.
03
Reliability Engineering and Risk Assessment
This track addresses the principles of reliability engineering and their application in risk assessment across different sectors. Contributions should focus on statistical methods for evaluating and improving system reliability and safety.
04
Innovative Sampling Methods for Quality Improvement
This session invites discussions on novel sampling techniques that enhance quality control processes. Papers should present theoretical advancements and practical applications of sampling methods in industrial settings.
05
Design of Experiments in Industrial Applications
This track emphasizes the role of design of experiments (DOE) in optimizing industrial processes. Researchers are encouraged to share their insights on experimental designs that lead to significant quality improvements and cost reductions.
06
Statistical Modeling for Process Control
This session focuses on the development and application of statistical models for effective process control. Contributions should demonstrate how modeling techniques can be utilized to enhance decision-making in industrial environments.
07
Quality Improvement Strategies in Production Systems
This track examines various strategies for quality improvement within production systems. Papers should explore systematic approaches and tools that lead to enhanced product quality and operational performance.
08
Manufacturing Statistics: Trends and Innovations
This session highlights emerging trends and innovative practices in the field of manufacturing statistics. Researchers are invited to present studies that showcase the application of statistical methods in improving manufacturing processes.
09
Statistical Process Control in Emerging Industries
This track investigates the application of statistical process control (SPC) techniques in emerging industries such as biotechnology and renewable energy. Contributions should focus on the unique challenges and solutions in these rapidly evolving sectors.
10
Quality Assurance through Statistical Analysis
This session emphasizes the importance of statistical analysis in ensuring quality assurance across various industries. Papers should discuss methodologies that leverage statistical tools to monitor and improve quality standards.
11
Integrating Statistical Methods with Industry 4.0
This track explores the intersection of statistical methods and Industry 4.0 technologies. Researchers are encouraged to present innovative approaches that utilize big data analytics and machine learning for enhanced quality control and process optimization.