General Manager - Industrial Engineering (Bhaluka, Mymensingh)

Job Description

Title: General Manager - Industrial Engineering (Bhaluka, Mymensingh)

Company Name: SQ Group

Vacancy: 1

Age: 30 to 40 years

Job Location: Mymensingh (Bhaluka)

Salary: Negotiable

Experience:

• 10 to 15 years
• The applicants should have experience in the following business area(s): Garments

• Bachelor of Science (BSc) in Industrial Eng & Production
• Master of Science (MSc) in Industrial Eng & Production

• 10 to 15 years
• The applicants should have experience in the following business area(s): Garments

• Age 30 to 40 years

• Professional certifications such as Lean Six Sigma (Green/Black Belt) or Kaizen / TPM / 5S training are preferred.

• 10-15 years of experience in garment manufacturing, with at least 3 years leading IE at factory or group level.

• Hands-on experience with GSD (General Sewing Data) - implementation, data maintenance, and SMV validation.

• Proven experience in Lean Manufacturing, work-study, and process improvement

• Lead the overall Industrial Engineering function across factories and manufacturing units.

• Develop and implement IE strategies, systems, standards, and performance measures aligned with business objectives.

• Drive improvements in productivity, efficiency, manpower utilization, machine utilization, capacity, and manufacturing cost.

• Standardize IE practices, methods, performance measurement, and improvement systems across manufacturing units.

• Monitor IE performance and identify opportunities for productivity and cost improvement.

• Establish and maintain a culture of continuous improvement, Kaizen, 5S, waste reduction, and problem solving.

• Identify bottlenecks, process losses, and non-value-added activities and drive improvement initiatives.

• Establish improvement frameworks, KPIs, and governance mechanisms for Lean and Operational Excellence programs.

• Benchmark manufacturing processes and performance to identify improvement opportunities.

• Develop and implement the digital manufacturing strategy in line with business and operational requirements.

• Identify opportunities to use digital technologies to improve production visibility, productivity, quality, and decision-making.

• Lead Industry 4.0 initiatives across manufacturing units, including connected processes, digital monitoring, and real-time performance management.

• Evaluate and implement suitable digital manufacturing solutions and technologies.

• Develop an automation strategy based on productivity, quality, cost, safety, and operational requirements.

• Identify processes suitable for automation and prioritize automation opportunities based on business value.

• Lead the evaluation, selection, and implementation of automation technologies and equipment.

• Work with Technical, Production, Engineering, and other relevant teams to ensure successful implementation.

• Evaluate investment requirements, expected productivity gains, and return on investment for automation projects.

• Identify practical applications of Artificial Intelligence and Machine Learning in manufacturing operations.

• Lead the implementation of AI-enabled solutions for forecasting, productivity analysis, quality monitoring, capacity planning, and operational decision-making.

• Develop or support data-driven decision support systems for management and operational teams.

• Work with IT, data, and functional teams to ensure AI solutions address actual business and manufacturing requirements.

• Review existing business and manufacturing processes to identify inefficiencies and improvement opportunities.

• Redesign workflows and operating processes based on business requirements, data, and performance analysis.

• Drive cross-functional productivity improvement programs across manufacturing operations.

• Establish measurable targets and monitor the results of transformation initiatives.

• Establish effective data governance practices for manufacturing and operational performance data.

• Develop standardized definitions, data structures, reporting methods, and performance measures.

• Lead the development of dashboards and real-time performance monitoring systems.

• Use operational data and analytics to identify performance gaps, trends, bottlenecks, and improvement opportunities.

• Promote data-driven decision-making across manufacturing functions.

• Lead change management activities associated with operational, digital, automation, and process transformation initiatives.

• Communicate transformation objectives, expected benefits, and implementation requirements to relevant stakeholders.

• Build organizational capability in Lean, IE, digital tools, data analytics, automation, and continuous improvement.

• Develop and implement training and capability-building programs for IE and operational teams.

• Lead transformation initiatives across Planning, Production, Quality, Technical, Supply Chain, and Manufacturing Operations.

• Work with functional heads to identify operational challenges and develop improvement solutions.

• Align transformation priorities across departments and ensure effective execution.

• Establish cross-functional project teams for major productivity, digitalization, automation, and process improvement initiatives.

• Establish governance structures for enterprise-wide transformation programs.

• Develop project priorities, implementation roadmaps, KPIs, and performance targets.

• Review progress of major transformation initiatives and ensure corrective actions are taken where required.

• Monitor financial and operational benefits generated through transformation projects.