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Open nowPosted 13 days ago

Global Smart Manufacturing Manager

MSA, The Safety Company117 open roles

Where
Cranberry Township, Pennsylvania, United States
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Your applicationOpen nowGlobal Smart Manufacturing ManagerMSA, The Safety Company · Cranberry Township, Pennsylvania, United States

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  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on MSA, The Safety Company's own form.

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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. MSA, The Safety Company postings stay open a median of 2 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: posted 13 days ago

MSA, The Safety Company median: 2 days open

The posting

Overview Are you someone who is passionate, motivated, and driven to make a difference? If so, MSA Safety is the perfect fit for your career. At MSA, SAFETY is who we are AND it is what we do. We are a purpose-driven company committed to deploying innovation and technology to deliver on our Mission to help protect people and assets all around the world. We continue to be relentless in our pursuit of solving our customers greatest problems so they can go home safe each and every day. Are you in? Read on for more details about this particular role. Responsibilities We are looking for a subject matter expert with applicable experience within a manufacturing leadership role. Define and execute MSA's global Factory of the Future technology vision. Develop and prioritize Industry 4.0 initiatives that align with business objectives and operational strategies. Identify emerging technologies and assess their potential to create business value across the manufacturing network. Partner with executive leadership to establish digital manufacturing priorities, investment strategies, and long-term transformation plans. Drive enterprise-wide adoption of innovative manufacturing technologies that improve competitiveness and operational agility. Partner with plant leadership to identify, prioritize, and implement high-value digital manufacturing opportunities. Communicate strategy, progress, risks, and business outcomes to senior leadership and key stakeholders. Develop multi-year capital investment plans supporting Factory of the Future technologies. Lead the evaluation, development, and deployment of scalable advanced manufacturing technologies, including MES, IIoT, AI/ML, Digital Twins, automation, analytics platforms, ERP integrated solutions, robotics, Cobots, AMRs/AGVs. Develop tools, templates and framework to evaluate new technologies and factories readiness for the scalable technology. Establish engineering standards and best practices for deploying. Oversee implementation of scalable digital manufacturing solutions across global manufacturing facilities. Steer partnership with data scientists, AI engineers, and business leaders to identify high-value applications including predictive maintenance, process optimization, vision inspection, and digital process control. Ensure seamless integration of shop-floor equipment, automation systems, manufacturing data, and enterprise platforms. Drive standardization of system architectures, connectivity models, and technology platforms to support a connected manufacturing ecosystem. Support equipment procurement, commissioning, qualification, validation, and technology readiness activities. Collaborate with internal stakeholders and external technology partners to develop and deploy innovative manufacturing solutions. Lead cross-functional teams through technology assessments, pilot programs, and global rollouts. Lead, mentor, and develop a high-performing global team of smart manufacturing, automation, analytics, and digital technology experts. Build organizational capabilities in digital manufacturing, AI, data analytics,and Industry 4.0 technologies. Foster a culture of innovation, knowledge sharing, technical excellence, and continuous learning. Support workforce adoption of new technologies through training, change management, and leadership engagement. Drive succession planning and capability development to meet future manufacturing technology needs. Establish and maintain global standards, governance frameworks, and best practices for smart manufacturing technologies and digital systems. Ensure consistent deployment methodologies, performance metrics, and technology management processes across all manufacturing locations. Establish and govern global manufacturing technology standards, MES templates, automation architectures, and digital deployment methodologies. Lead efforts to improve manufacturing productivity, quality, asset utilization, reliability, and cost performance through data-driven decision making. Promote disciplined process documentation, system lifecycle management, and continuous improvement practices. Develop business cases, capital investment proposals, and ROI models to prioritize and justify digital manufacturing initiatives Monitor and measure the financial and operational impact of smart manufacturing initiatives. Qualifications Required Experience: Experience and strong knowledge of: Digital Manufacturing Applications (MES), Industrial IoT (IIot), Automation and Controls Systems, SCADA and PLC environments, Data analytics and visualization tools, ERP integration (SAP), Robotics & cobots. Demonstrated ability to successfully manage and implement Industry 4.0 projects with positive financial impact from the solution. Driving and ensuring regular process documentation is developed and maintained. Multinational manufacturing environment experience. Experience in manufacturing equipment procurement, setup and commissioning, including a clear understanding of equipment/software qualification and validation processes. Proven track record of leading cross-functional teams in the development and optimization of new technologies. Strong communication skills with the ability to collaborate effectively with multidisciplinary teams and convey technical concepts to diverse stakeholders. Organizational change management KPI ownership Vendor management Experience Preferred: Experience and knowledge of: Machine Learning, Industrial connectivity architectures, AI in manufacturing, Digital Twins, Advanced vision systems, AMRs/AGVs. Deploying AI/ML solutions in production environments with an understanding of cloud manufacturing platforms including but not limited to: (Azure, AWS, Snowflake) Developing a multi-year digital manufacturing roadmap including capital investment planning, ROI modeling, and prioritization. Creating governance models of global manufacturing systems including but not limited to: data architecture, data quality management, master data governance, historian strategies, and data ownership models. Working with data scientist & AI engineers to develop manufacturing solutions and creating prioritization of those AI use cases. Some applications could include: predictive maintenance, process optimization, computer vision quality inspection, and digital process control. Connecting shop-floor machines to enterprise systems. Developing digital skills within manufacturing organizations, influencing plant leadership and driving workforce adoption with stakeholder engagement. Apply advanced engineering principles and process control strategies to improve operating efficiency of new and existing automation systems. Understanding of common Manufacturing/Operations technology cybersecurity requirements: Industrial network security, ISA/IEC 62443 familiarity, Operations Technology cybersecurity risk assessments. Proven ability to drive technology at scale across 20+ facilities including developing standard automation platforms, global equipment catalogs, MES templates, KPI governance. Education Required: B,S. in Engineering from an ABET-accredited program. This position is available at two different career levels based upon individual qualifications, experience, and education: Level II Engineering Manager: 10 years relevant experience including a minimum of 2 years' experience in direct staff management. Senior Engineering Manager: 12 years relevant experience including a minimum of 2 years' experience in direct staff management. MS degree may be substituted for up to 2 years of relevant experience; PhD may be substituted for up to 4 years. Education Preferred: MBA, Operations certification a plus, such as lean systems Continuing Education in Management studies PMP certification #LI-GM1

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